Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Liang Chen]

+ 1 (non-binding) 

Regards
Liang



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[RESULT] [VOTE] Accept PredictionIO into the Apache Incubator

[Andrew Purtell]

​The ​
VOTE
​ to

​a
ccept PredictionIO into the Apache Incubator
​ has concluded and passed with 20 binding +1s, 8 non-binding +1s, and no 0
or -1 votes.

​Thanks to all who voted.

Binding +1s

Andrew Purtell
​Luciano Resende
James Taylor
Suneel Marthi
​Chris Nauroth
Roman Shaposhnik
Ted Dunning
Henry Saputra
​Drew Farris​
Jean-Baptiste Onofré
Uma Gangumalla
Sergio Fernández
John D. Ament
Ralph Goers
Seetharam Venkatesh
Hitesh Shah
Jake Farrell
Reynold Xin
Paul Fremantle
Bertrand Delacretaz

Nonbinding +1s

Ashish
Debo Dutta
Felix Cheung
Priyank Ashok Rastogi
Moon Soo Lee
Alexander Bezzubov
Tsuyoshi Ozawa
Sandeep Deshmukh

​No binding or nonbinding 0s

No binding or nonbinding -1s
​

--

Best regards,

   - Andy

Problems worthy of attack prove their worth by hitting back. - Piet Hein
(via Tom White)

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Bertrand Delacretaz]

On Tue, May 24, 2016 at 12:22 AM, Andrew Purtell  wrote:
> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator...

+1

-Bertrand

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Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Sandeep Deshmukh]

+ 1 (non-binding)

Regards,
Sandeep

On Wed, May 25, 2016 at 10:38 AM, Paul Fremantle  wrote:

> +1 (binding)
> Paul
>
> On Wed, May 25, 2016 at 5:12 AM, Tsuyoshi Ozawa  wrote:
>
> > +1 (non-binding)
> > - Tsuyoshi
> >
> > On Wed, May 25, 2016 at 1:00 PM, Reynold Xin 
> wrote:
> > > +1 (binding)
> > >
> > >
> > > On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell 
> > wrote:
> > >
> > >> Since discussion on the matter of PredictionIO has died down, I would
> > like
> > >> to call a VOTE
> > >> on accepting PredictionIO into the Apache Incubator.
> > >>
> > >> Proposal: https://wiki.apache.org/incubator/PredictionIO
> > >>
> > >> [ ] +1 Accept PredictionIO into the Apache Incubator
> > >> [ ] +0 Abstain
> > >> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because
> ...
> > >>
> > >> This vote will be open for at least 72 hours.
> > >>
> > >> My vote is +1 (binding)
> > >>
> > >> --
> > >>
> > >> PredictionIO Proposal
> > >>
> > >> Abstract
> > >>
> > >> PredictionIO is an open source Machine Learning Server built on top of
> > >> state-of-the-art open source stack, that enables developers to manage
> > and
> > >> deploy production-ready predictive services for various kinds of
> machine
> > >> learning tasks.
> > >>
> > >> Proposal
> > >>
> > >> The PredictionIO platform consists of the following components:
> > >>
> > >>* PredictionIO framework - provides the machine learning stack for
> > >>  building, evaluating and deploying engines with machine learning
> > >>  algorithms. It uses Apache Spark for processing.
> > >>
> > >>* Event Server - the machine learning analytics layer for unifying
> > >> events
> > >>  from multiple platforms. It can use Apache HBase or any JDBC
> > backends
> > >>  as its data store.
> > >>
> > >> The PredictionIO community also maintains a Template Gallery, a place
> to
> > >> publish and download (free or proprietary) engine templates for
> > different
> > >> types of machine learning applications, and is a complemental part of
> > the
> > >> project. At this point we exclude the Template Gallery from the
> > proposal,
> > >> as it has a separate set of contributors and we’re not familiar with
> an
> > >> Apache approved mechanism to maintain such a gallery.
> > >>
> > >> Background
> > >>
> > >> PredictionIO was started with a mission to democratize and bring
> machine
> > >> learning to the masses.
> > >>
> > >> Machine learning has traditionally been a luxury for big companies
> like
> > >> Google, Facebook, and Netflix. There are ML libraries and tools lying
> > >> around the internet but the effort of putting them all together as a
> > >> production-ready infrastructure is a very resource-intensive task that
> > is
> > >> remotely reachable by individuals or small businesses.
> > >>
> > >> PredictionIO is a production-ready, full stack machine learning system
> > that
> > >> allows organizations of any scale to quickly deploy machine learning
> > >> capabilities. It comes with official and community-contributed machine
> > >> learning engine templates that are easy to customize.
> > >>
> > >> Rationale
> > >>
> > >> As usage and number of contributors to PredictionIO has grown bigger
> and
> > >> more diverse, we have sought for an independent framework for the
> > project
> > >> to keep thriving. We believe the Apache foundation is a great fit.
> > Joining
> > >> Apache would ensure that tried and true processes and procedures are
> in
> > >> place for the growing number of organizations interested in
> contributing
> > >> to PredictionIO. PredictionIO is also a good fit for the Apache
> > foundation.
> > >> PredictionIO was built on top of several Apache projects (HBase,
> Spark,
> > >> Hadoop). We are familiar with the Apache process and believe that the
> > >> democratic and meritocratic nature of the foundation aligns with the
> > >> project goals.
> > >>
> > >> Initial Goals
> > >>
> > >> The initial milestones will be to move the existing codebase to Apache
> > and
> > >> integrate with the Apache development process. Once this is
> > accomplished,
> > >> we plan for incremental development and releases that follow the
> Apache
> > >> guidelines, as well as growing our developer and user communities.
> > >>
> > >> Current Status
> > >>
> > >> PredictionIO has undergone nine minor releases and many patches.
> > >> PredictionIO is being used in production by Salesforce.com as well as
> > many
> > >> other organizations and apps. The PredictionIO codebase is currently
> > >> hosted at GitHub, which will form the basis of the Apache git
> > repository.
> > >>
> > >> Meritocracy
> > >>
> > >> We plan to invest in supporting a meritocracy. We will discuss the
> > >> requirements in an open forum. We intend to invite additional
> developers
> > >> to participate. We will encourage and monitor community participation
> so
> > >> that privileges can be 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Paul Fremantle]

+1 (binding)
Paul

On Wed, May 25, 2016 at 5:12 AM, Tsuyoshi Ozawa  wrote:

> +1 (non-binding)
> - Tsuyoshi
>
> On Wed, May 25, 2016 at 1:00 PM, Reynold Xin  wrote:
> > +1 (binding)
> >
> >
> > On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell 
> wrote:
> >
> >> Since discussion on the matter of PredictionIO has died down, I would
> like
> >> to call a VOTE
> >> on accepting PredictionIO into the Apache Incubator.
> >>
> >> Proposal: https://wiki.apache.org/incubator/PredictionIO
> >>
> >> [ ] +1 Accept PredictionIO into the Apache Incubator
> >> [ ] +0 Abstain
> >> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> >>
> >> This vote will be open for at least 72 hours.
> >>
> >> My vote is +1 (binding)
> >>
> >> --
> >>
> >> PredictionIO Proposal
> >>
> >> Abstract
> >>
> >> PredictionIO is an open source Machine Learning Server built on top of
> >> state-of-the-art open source stack, that enables developers to manage
> and
> >> deploy production-ready predictive services for various kinds of machine
> >> learning tasks.
> >>
> >> Proposal
> >>
> >> The PredictionIO platform consists of the following components:
> >>
> >>* PredictionIO framework - provides the machine learning stack for
> >>  building, evaluating and deploying engines with machine learning
> >>  algorithms. It uses Apache Spark for processing.
> >>
> >>* Event Server - the machine learning analytics layer for unifying
> >> events
> >>  from multiple platforms. It can use Apache HBase or any JDBC
> backends
> >>  as its data store.
> >>
> >> The PredictionIO community also maintains a Template Gallery, a place to
> >> publish and download (free or proprietary) engine templates for
> different
> >> types of machine learning applications, and is a complemental part of
> the
> >> project. At this point we exclude the Template Gallery from the
> proposal,
> >> as it has a separate set of contributors and we’re not familiar with an
> >> Apache approved mechanism to maintain such a gallery.
> >>
> >> Background
> >>
> >> PredictionIO was started with a mission to democratize and bring machine
> >> learning to the masses.
> >>
> >> Machine learning has traditionally been a luxury for big companies like
> >> Google, Facebook, and Netflix. There are ML libraries and tools lying
> >> around the internet but the effort of putting them all together as a
> >> production-ready infrastructure is a very resource-intensive task that
> is
> >> remotely reachable by individuals or small businesses.
> >>
> >> PredictionIO is a production-ready, full stack machine learning system
> that
> >> allows organizations of any scale to quickly deploy machine learning
> >> capabilities. It comes with official and community-contributed machine
> >> learning engine templates that are easy to customize.
> >>
> >> Rationale
> >>
> >> As usage and number of contributors to PredictionIO has grown bigger and
> >> more diverse, we have sought for an independent framework for the
> project
> >> to keep thriving. We believe the Apache foundation is a great fit.
> Joining
> >> Apache would ensure that tried and true processes and procedures are in
> >> place for the growing number of organizations interested in contributing
> >> to PredictionIO. PredictionIO is also a good fit for the Apache
> foundation.
> >> PredictionIO was built on top of several Apache projects (HBase, Spark,
> >> Hadoop). We are familiar with the Apache process and believe that the
> >> democratic and meritocratic nature of the foundation aligns with the
> >> project goals.
> >>
> >> Initial Goals
> >>
> >> The initial milestones will be to move the existing codebase to Apache
> and
> >> integrate with the Apache development process. Once this is
> accomplished,
> >> we plan for incremental development and releases that follow the Apache
> >> guidelines, as well as growing our developer and user communities.
> >>
> >> Current Status
> >>
> >> PredictionIO has undergone nine minor releases and many patches.
> >> PredictionIO is being used in production by Salesforce.com as well as
> many
> >> other organizations and apps. The PredictionIO codebase is currently
> >> hosted at GitHub, which will form the basis of the Apache git
> repository.
> >>
> >> Meritocracy
> >>
> >> We plan to invest in supporting a meritocracy. We will discuss the
> >> requirements in an open forum. We intend to invite additional developers
> >> to participate. We will encourage and monitor community participation so
> >> that privileges can be extended to those that contribute.
> >>
> >> Community
> >>
> >> Acceptance into the Apache foundation would bolster the already strong
> >> user and developer community around PredictionIO. That community
> includes
> >> many contributors from various other companies, and an active mailing
> list
> >> composed of hundreds of users.
> >>
> >> Core Developers
> >>
> >> The core developers of 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Tsuyoshi Ozawa]

+1 (non-binding)
- Tsuyoshi

On Wed, May 25, 2016 at 1:00 PM, Reynold Xin  wrote:
> +1 (binding)
>
>
> On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell  wrote:
>
>> Since discussion on the matter of PredictionIO has died down, I would like
>> to call a VOTE
>> on accepting PredictionIO into the Apache Incubator.
>>
>> Proposal: https://wiki.apache.org/incubator/PredictionIO
>>
>> [ ] +1 Accept PredictionIO into the Apache Incubator
>> [ ] +0 Abstain
>> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>>
>> This vote will be open for at least 72 hours.
>>
>> My vote is +1 (binding)
>>
>> --
>>
>> PredictionIO Proposal
>>
>> Abstract
>>
>> PredictionIO is an open source Machine Learning Server built on top of
>> state-of-the-art open source stack, that enables developers to manage and
>> deploy production-ready predictive services for various kinds of machine
>> learning tasks.
>>
>> Proposal
>>
>> The PredictionIO platform consists of the following components:
>>
>>* PredictionIO framework - provides the machine learning stack for
>>  building, evaluating and deploying engines with machine learning
>>  algorithms. It uses Apache Spark for processing.
>>
>>* Event Server - the machine learning analytics layer for unifying
>> events
>>  from multiple platforms. It can use Apache HBase or any JDBC backends
>>  as its data store.
>>
>> The PredictionIO community also maintains a Template Gallery, a place to
>> publish and download (free or proprietary) engine templates for different
>> types of machine learning applications, and is a complemental part of the
>> project. At this point we exclude the Template Gallery from the proposal,
>> as it has a separate set of contributors and we’re not familiar with an
>> Apache approved mechanism to maintain such a gallery.
>>
>> Background
>>
>> PredictionIO was started with a mission to democratize and bring machine
>> learning to the masses.
>>
>> Machine learning has traditionally been a luxury for big companies like
>> Google, Facebook, and Netflix. There are ML libraries and tools lying
>> around the internet but the effort of putting them all together as a
>> production-ready infrastructure is a very resource-intensive task that is
>> remotely reachable by individuals or small businesses.
>>
>> PredictionIO is a production-ready, full stack machine learning system that
>> allows organizations of any scale to quickly deploy machine learning
>> capabilities. It comes with official and community-contributed machine
>> learning engine templates that are easy to customize.
>>
>> Rationale
>>
>> As usage and number of contributors to PredictionIO has grown bigger and
>> more diverse, we have sought for an independent framework for the project
>> to keep thriving. We believe the Apache foundation is a great fit. Joining
>> Apache would ensure that tried and true processes and procedures are in
>> place for the growing number of organizations interested in contributing
>> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
>> PredictionIO was built on top of several Apache projects (HBase, Spark,
>> Hadoop). We are familiar with the Apache process and believe that the
>> democratic and meritocratic nature of the foundation aligns with the
>> project goals.
>>
>> Initial Goals
>>
>> The initial milestones will be to move the existing codebase to Apache and
>> integrate with the Apache development process. Once this is accomplished,
>> we plan for incremental development and releases that follow the Apache
>> guidelines, as well as growing our developer and user communities.
>>
>> Current Status
>>
>> PredictionIO has undergone nine minor releases and many patches.
>> PredictionIO is being used in production by Salesforce.com as well as many
>> other organizations and apps. The PredictionIO codebase is currently
>> hosted at GitHub, which will form the basis of the Apache git repository.
>>
>> Meritocracy
>>
>> We plan to invest in supporting a meritocracy. We will discuss the
>> requirements in an open forum. We intend to invite additional developers
>> to participate. We will encourage and monitor community participation so
>> that privileges can be extended to those that contribute.
>>
>> Community
>>
>> Acceptance into the Apache foundation would bolster the already strong
>> user and developer community around PredictionIO. That community includes
>> many contributors from various other companies, and an active mailing list
>> composed of hundreds of users.
>>
>> Core Developers
>>
>> The core developers of our project are listed in our contributors and
>> initial PPMC below. Though many are employed at Salesforce.com, there are
>> also engineers from ActionML, and independent developers.
>>
>> Alignment
>>
>> The ASF is the natural choice to host the PredictionIO project as its goal
>> is democratizing Machine Learning by making it more easily accessible to

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Reynold Xin]

+1 (binding)


On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell  wrote:

> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>
> PredictionIO Proposal
>
> Abstract
>
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
>
> Proposal
>
> The PredictionIO platform consists of the following components:
>
>* PredictionIO framework - provides the machine learning stack for
>  building, evaluating and deploying engines with machine learning
>  algorithms. It uses Apache Spark for processing.
>
>* Event Server - the machine learning analytics layer for unifying
> events
>  from multiple platforms. It can use Apache HBase or any JDBC backends
>  as its data store.
>
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
>
> Background
>
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
>
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
>
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
>
> Rationale
>
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
>
> Initial Goals
>
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
>
> Current Status
>
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
>
> Meritocracy
>
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
>
> Community
>
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
>
> Core Developers
>
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
>
> Alignment
>
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
>
> Known Risks
>
> Orphaned Products
>
> PredictionIO has a solid and growing community. It is deployed on
> 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Jake Farrell]

+1

-Jake

On Mon, May 23, 2016 at 6:22 PM, Andrew Purtell  wrote:

> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>
> PredictionIO Proposal
>
> Abstract
>
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
>
> Proposal
>
> The PredictionIO platform consists of the following components:
>
>* PredictionIO framework - provides the machine learning stack for
>  building, evaluating and deploying engines with machine learning
>  algorithms. It uses Apache Spark for processing.
>
>* Event Server - the machine learning analytics layer for unifying
> events
>  from multiple platforms. It can use Apache HBase or any JDBC backends
>  as its data store.
>
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
>
> Background
>
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
>
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
>
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
>
> Rationale
>
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
>
> Initial Goals
>
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
>
> Current Status
>
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
>
> Meritocracy
>
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
>
> Community
>
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
>
> Core Developers
>
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
>
> Alignment
>
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
>
> Known Risks
>
> Orphaned Products
>
> PredictionIO has a solid and growing community. It is deployed on
> 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Hitesh Shah]

+1 (binding)

— Hitesh

> On May 23, 2016, at 3:22 PM, Andrew Purtell  wrote:
> 
> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
> 
> Proposal: https://wiki.apache.org/incubator/PredictionIO
> 
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> 
> This vote will be open for at least 72 hours.
> 
> My vote is +1 (binding)
> 
> --
> 
> PredictionIO Proposal
> 
> Abstract
> 
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
> 
> Proposal
> 
> The PredictionIO platform consists of the following components:
> 
>   * PredictionIO framework - provides the machine learning stack for
> building, evaluating and deploying engines with machine learning
> algorithms. It uses Apache Spark for processing.
> 
>   * Event Server - the machine learning analytics layer for unifying events
> from multiple platforms. It can use Apache HBase or any JDBC backends
> as its data store.
> 
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
> 
> Background
> 
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
> 
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
> 
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
> 
> Rationale
> 
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
> 
> Initial Goals
> 
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
> 
> Current Status
> 
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
> 
> Meritocracy
> 
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
> 
> Community
> 
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
> 
> Core Developers
> 
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
> 
> Alignment
> 
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
> 
> Known Risks
> 
> Orphaned Products
> 
> PredictionIO has a solid and 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Seetharam Venkatesh]

+1 (binding)

All the best,
Venkatesh

On Tue, May 24, 2016 at 7:15 AM Ralph Goers 
wrote:

> +1 (binding)
>
> Ralph
>
> > On May 24, 2016, at 3:44 AM, John D. Ament 
> wrote:
> >
> > +1
> >
> > On Mon, May 23, 2016 at 6:23 PM Andrew Purtell 
> wrote:
> >
> >> Since discussion on the matter of PredictionIO has died down, I would
> like
> >> to call a VOTE
> >> on accepting PredictionIO into the Apache Incubator.
> >>
> >> Proposal: https://wiki.apache.org/incubator/PredictionIO
> >>
> >> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> >> [ ] +0 Abstain
> >> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> >>
> >> This vote will be open for at least 72 hours.
> >>
> >> My vote is +1 (binding)
> >>
> >> --
> >>
> >> PredictionIO Proposal
> >>
> >> Abstract
> >>
> >> PredictionIO is an open source Machine Learning Server built on top of
> >> state-of-the-art open source stack, that enables developers to manage
> and
> >> deploy production-ready predictive services for various kinds of machine
> >> learning tasks.
> >>
> >> Proposal
> >>
> >> The PredictionIO platform consists of the following components:
> >>
> >>   * PredictionIO framework - provides the machine learning stack for
> >> building, evaluating and deploying engines with machine learning
> >> algorithms. It uses Apache Spark for processing.
> >>
> >>   * Event Server - the machine learning analytics layer for unifying
> >> events
> >> from multiple platforms. It can use Apache HBase or any JDBC
> backends
> >> as its data store.
> >>
> >> The PredictionIO community also maintains a Template Gallery, a place to
> >> publish and download (free or proprietary) engine templates for
> different
> >> types of machine learning applications, and is a complemental part of
> the
> >> project. At this point we exclude the Template Gallery from the
> proposal,
> >> as it has a separate set of contributors and we’re not familiar with an
> >> Apache approved mechanism to maintain such a gallery.
> >>
> >> Background
> >>
> >> PredictionIO was started with a mission to democratize and bring machine
> >> learning to the masses.
> >>
> >> Machine learning has traditionally been a luxury for big companies like
> >> Google, Facebook, and Netflix. There are ML libraries and tools lying
> >> around the internet but the effort of putting them all together as a
> >> production-ready infrastructure is a very resource-intensive task that
> is
> >> remotely reachable by individuals or small businesses.
> >>
> >> PredictionIO is a production-ready, full stack machine learning system
> that
> >> allows organizations of any scale to quickly deploy machine learning
> >> capabilities. It comes with official and community-contributed machine
> >> learning engine templates that are easy to customize.
> >>
> >> Rationale
> >>
> >> As usage and number of contributors to PredictionIO has grown bigger and
> >> more diverse, we have sought for an independent framework for the
> project
> >> to keep thriving. We believe the Apache foundation is a great fit.
> Joining
> >> Apache would ensure that tried and true processes and procedures are in
> >> place for the growing number of organizations interested in contributing
> >> to PredictionIO. PredictionIO is also a good fit for the Apache
> foundation.
> >> PredictionIO was built on top of several Apache projects (HBase, Spark,
> >> Hadoop). We are familiar with the Apache process and believe that the
> >> democratic and meritocratic nature of the foundation aligns with the
> >> project goals.
> >>
> >> Initial Goals
> >>
> >> The initial milestones will be to move the existing codebase to Apache
> and
> >> integrate with the Apache development process. Once this is
> accomplished,
> >> we plan for incremental development and releases that follow the Apache
> >> guidelines, as well as growing our developer and user communities.
> >>
> >> Current Status
> >>
> >> PredictionIO has undergone nine minor releases and many patches.
> >> PredictionIO is being used in production by Salesforce.com as well as
> many
> >> other organizations and apps. The PredictionIO codebase is currently
> >> hosted at GitHub, which will form the basis of the Apache git
> repository.
> >>
> >> Meritocracy
> >>
> >> We plan to invest in supporting a meritocracy. We will discuss the
> >> requirements in an open forum. We intend to invite additional developers
> >> to participate. We will encourage and monitor community participation so
> >> that privileges can be extended to those that contribute.
> >>
> >> Community
> >>
> >> Acceptance into the Apache foundation would bolster the already strong
> >> user and developer community around PredictionIO. That community
> includes
> >> many contributors from various other companies, and an active mailing
> list
> >> composed of hundreds of users.
> >>
> >> Core Developers
> >>
> >> The core 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Ralph Goers]

+1 (binding)

Ralph

> On May 24, 2016, at 3:44 AM, John D. Ament  wrote:
> 
> +1
> 
> On Mon, May 23, 2016 at 6:23 PM Andrew Purtell  wrote:
> 
>> Since discussion on the matter of PredictionIO has died down, I would like
>> to call a VOTE
>> on accepting PredictionIO into the Apache Incubator.
>> 
>> Proposal: https://wiki.apache.org/incubator/PredictionIO
>> 
>> ​[ ] +1 Accept PredictionIO into the Apache Incubator
>> [ ] +0 Abstain
>> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>> 
>> This vote will be open for at least 72 hours.
>> 
>> My vote is +1 (binding)
>> 
>> --
>> 
>> PredictionIO Proposal
>> 
>> Abstract
>> 
>> PredictionIO is an open source Machine Learning Server built on top of
>> state-of-the-art open source stack, that enables developers to manage and
>> deploy production-ready predictive services for various kinds of machine
>> learning tasks.
>> 
>> Proposal
>> 
>> The PredictionIO platform consists of the following components:
>> 
>>   * PredictionIO framework - provides the machine learning stack for
>> building, evaluating and deploying engines with machine learning
>> algorithms. It uses Apache Spark for processing.
>> 
>>   * Event Server - the machine learning analytics layer for unifying
>> events
>> from multiple platforms. It can use Apache HBase or any JDBC backends
>> as its data store.
>> 
>> The PredictionIO community also maintains a Template Gallery, a place to
>> publish and download (free or proprietary) engine templates for different
>> types of machine learning applications, and is a complemental part of the
>> project. At this point we exclude the Template Gallery from the proposal,
>> as it has a separate set of contributors and we’re not familiar with an
>> Apache approved mechanism to maintain such a gallery.
>> 
>> Background
>> 
>> PredictionIO was started with a mission to democratize and bring machine
>> learning to the masses.
>> 
>> Machine learning has traditionally been a luxury for big companies like
>> Google, Facebook, and Netflix. There are ML libraries and tools lying
>> around the internet but the effort of putting them all together as a
>> production-ready infrastructure is a very resource-intensive task that is
>> remotely reachable by individuals or small businesses.
>> 
>> PredictionIO is a production-ready, full stack machine learning system that
>> allows organizations of any scale to quickly deploy machine learning
>> capabilities. It comes with official and community-contributed machine
>> learning engine templates that are easy to customize.
>> 
>> Rationale
>> 
>> As usage and number of contributors to PredictionIO has grown bigger and
>> more diverse, we have sought for an independent framework for the project
>> to keep thriving. We believe the Apache foundation is a great fit. Joining
>> Apache would ensure that tried and true processes and procedures are in
>> place for the growing number of organizations interested in contributing
>> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
>> PredictionIO was built on top of several Apache projects (HBase, Spark,
>> Hadoop). We are familiar with the Apache process and believe that the
>> democratic and meritocratic nature of the foundation aligns with the
>> project goals.
>> 
>> Initial Goals
>> 
>> The initial milestones will be to move the existing codebase to Apache and
>> integrate with the Apache development process. Once this is accomplished,
>> we plan for incremental development and releases that follow the Apache
>> guidelines, as well as growing our developer and user communities.
>> 
>> Current Status
>> 
>> PredictionIO has undergone nine minor releases and many patches.
>> PredictionIO is being used in production by Salesforce.com as well as many
>> other organizations and apps. The PredictionIO codebase is currently
>> hosted at GitHub, which will form the basis of the Apache git repository.
>> 
>> Meritocracy
>> 
>> We plan to invest in supporting a meritocracy. We will discuss the
>> requirements in an open forum. We intend to invite additional developers
>> to participate. We will encourage and monitor community participation so
>> that privileges can be extended to those that contribute.
>> 
>> Community
>> 
>> Acceptance into the Apache foundation would bolster the already strong
>> user and developer community around PredictionIO. That community includes
>> many contributors from various other companies, and an active mailing list
>> composed of hundreds of users.
>> 
>> Core Developers
>> 
>> The core developers of our project are listed in our contributors and
>> initial PPMC below. Though many are employed at Salesforce.com, there are
>> also engineers from ActionML, and independent developers.
>> 
>> Alignment
>> 
>> The ASF is the natural choice to host the PredictionIO project as its goal
>> is democratizing Machine Learning by making it more easily 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[John D. Ament]

+1

On Mon, May 23, 2016 at 6:23 PM Andrew Purtell  wrote:

> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>
> PredictionIO Proposal
>
> Abstract
>
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
>
> Proposal
>
> The PredictionIO platform consists of the following components:
>
>* PredictionIO framework - provides the machine learning stack for
>  building, evaluating and deploying engines with machine learning
>  algorithms. It uses Apache Spark for processing.
>
>* Event Server - the machine learning analytics layer for unifying
> events
>  from multiple platforms. It can use Apache HBase or any JDBC backends
>  as its data store.
>
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
>
> Background
>
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
>
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
>
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
>
> Rationale
>
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
>
> Initial Goals
>
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
>
> Current Status
>
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
>
> Meritocracy
>
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
>
> Community
>
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
>
> Core Developers
>
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
>
> Alignment
>
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
>
> Known Risks
>
> Orphaned Products
>
> PredictionIO has a solid and growing community. It is deployed on
> production 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Sergio Fernández]

+1 (binding)

On Tue, May 24, 2016 at 12:22 AM, Andrew Purtell 
wrote:

> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>
> PredictionIO Proposal
>
> Abstract
>
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
>
> Proposal
>
> The PredictionIO platform consists of the following components:
>
>* PredictionIO framework - provides the machine learning stack for
>  building, evaluating and deploying engines with machine learning
>  algorithms. It uses Apache Spark for processing.
>
>* Event Server - the machine learning analytics layer for unifying
> events
>  from multiple platforms. It can use Apache HBase or any JDBC backends
>  as its data store.
>
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
>
> Background
>
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
>
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
>
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
>
> Rationale
>
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
>
> Initial Goals
>
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
>
> Current Status
>
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
>
> Meritocracy
>
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
>
> Community
>
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
>
> Core Developers
>
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
>
> Alignment
>
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
>
> Known Risks
>
> Orphaned Products
>
> PredictionIO has a solid and growing community. It is deployed on
> 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Gangumalla, Uma]

+1 (binding)

Regards,
Uma

On 5/23/16, 3:22 PM, "Andrew Purtell"  wrote:

>Since discussion on the matter of PredictionIO has died down, I would like
>to call a VOTE
>on accepting PredictionIO into the Apache Incubator.
>
>Proposal: https://wiki.apache.org/incubator/PredictionIO
>
>​[ ] +1 Accept PredictionIO into the Apache Incubator
>[ ] +0 Abstain
>[ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
>This vote will be open for at least 72 hours.
>
>My vote is +1 (binding)
>
>--
>
>PredictionIO Proposal
>
>Abstract
>
>PredictionIO is an open source Machine Learning Server built on top of
>state-of-the-art open source stack, that enables developers to manage and
>deploy production-ready predictive services for various kinds of machine
>learning tasks.
>
>Proposal
>
>The PredictionIO platform consists of the following components:
>
>   * PredictionIO framework - provides the machine learning stack for
> building, evaluating and deploying engines with machine learning
> algorithms. It uses Apache Spark for processing.
>
>   * Event Server - the machine learning analytics layer for unifying
>events
> from multiple platforms. It can use Apache HBase or any JDBC backends
> as its data store.
>
>The PredictionIO community also maintains a Template Gallery, a place to
>publish and download (free or proprietary) engine templates for different
>types of machine learning applications, and is a complemental part of the
>project. At this point we exclude the Template Gallery from the proposal,
>as it has a separate set of contributors and we’re not familiar with an
>Apache approved mechanism to maintain such a gallery.
>
>Background
>
>PredictionIO was started with a mission to democratize and bring machine
>learning to the masses.
>
>Machine learning has traditionally been a luxury for big companies like
>Google, Facebook, and Netflix. There are ML libraries and tools lying
>around the internet but the effort of putting them all together as a
>production-ready infrastructure is a very resource-intensive task that is
>remotely reachable by individuals or small businesses.
>
>PredictionIO is a production-ready, full stack machine learning system
>that
>allows organizations of any scale to quickly deploy machine learning
>capabilities. It comes with official and community-contributed machine
>learning engine templates that are easy to customize.
>
>Rationale
>
>As usage and number of contributors to PredictionIO has grown bigger and
>more diverse, we have sought for an independent framework for the project
>to keep thriving. We believe the Apache foundation is a great fit. Joining
>Apache would ensure that tried and true processes and procedures are in
>place for the growing number of organizations interested in contributing
>to PredictionIO. PredictionIO is also a good fit for the Apache
>foundation.
>PredictionIO was built on top of several Apache projects (HBase, Spark,
>Hadoop). We are familiar with the Apache process and believe that the
>democratic and meritocratic nature of the foundation aligns with the
>project goals.
>
>Initial Goals
>
>The initial milestones will be to move the existing codebase to Apache and
>integrate with the Apache development process. Once this is accomplished,
>we plan for incremental development and releases that follow the Apache
>guidelines, as well as growing our developer and user communities.
>
>Current Status
>
>PredictionIO has undergone nine minor releases and many patches.
>PredictionIO is being used in production by Salesforce.com as well as many
>other organizations and apps. The PredictionIO codebase is currently
>hosted at GitHub, which will form the basis of the Apache git repository.
>
>Meritocracy
>
>We plan to invest in supporting a meritocracy. We will discuss the
>requirements in an open forum. We intend to invite additional developers
>to participate. We will encourage and monitor community participation so
>that privileges can be extended to those that contribute.
>
>Community
>
>Acceptance into the Apache foundation would bolster the already strong
>user and developer community around PredictionIO. That community includes
>many contributors from various other companies, and an active mailing list
>composed of hundreds of users.
>
>Core Developers
>
>The core developers of our project are listed in our contributors and
>initial PPMC below. Though many are employed at Salesforce.com, there are
>also engineers from ActionML, and independent developers.
>
>Alignment
>
>The ASF is the natural choice to host the PredictionIO project as its goal
>is democratizing Machine Learning by making it more easily accessible to
>every user/developer. PredictionIO is built on top of several top level
>Apache projects as outlined above.
>
>Known Risks
>
>Orphaned Products
>
>PredictionIO has a solid and growing community. It is deployed on
>production environments by companies of all sizes to run various kinds of

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Jean-Baptiste Onofré]

+1 (binding)

Regards
JB

On 05/24/2016 12:22 AM, Andrew Purtell wrote:

Since discussion on the matter of PredictionIO has died down, I would like
to call a VOTE
on accepting PredictionIO into the Apache Incubator.

Proposal: https://wiki.apache.org/incubator/PredictionIO

​[ ] +1 Accept PredictionIO into the Apache Incubator
[ ] +0 Abstain
[ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...

This vote will be open for at least 72 hours.

My vote is +1 (binding)

--

PredictionIO Proposal

Abstract

PredictionIO is an open source Machine Learning Server built on top of
state-of-the-art open source stack, that enables developers to manage and
deploy production-ready predictive services for various kinds of machine
learning tasks.

Proposal

The PredictionIO platform consists of the following components:

* PredictionIO framework - provides the machine learning stack for
  building, evaluating and deploying engines with machine learning
  algorithms. It uses Apache Spark for processing.

* Event Server - the machine learning analytics layer for unifying events
  from multiple platforms. It can use Apache HBase or any JDBC backends
  as its data store.

The PredictionIO community also maintains a Template Gallery, a place to
publish and download (free or proprietary) engine templates for different
types of machine learning applications, and is a complemental part of the
project. At this point we exclude the Template Gallery from the proposal,
as it has a separate set of contributors and we’re not familiar with an
Apache approved mechanism to maintain such a gallery.

Background

PredictionIO was started with a mission to democratize and bring machine
learning to the masses.

Machine learning has traditionally been a luxury for big companies like
Google, Facebook, and Netflix. There are ML libraries and tools lying
around the internet but the effort of putting them all together as a
production-ready infrastructure is a very resource-intensive task that is
remotely reachable by individuals or small businesses.

PredictionIO is a production-ready, full stack machine learning system that
allows organizations of any scale to quickly deploy machine learning
capabilities. It comes with official and community-contributed machine
learning engine templates that are easy to customize.

Rationale

As usage and number of contributors to PredictionIO has grown bigger and
more diverse, we have sought for an independent framework for the project
to keep thriving. We believe the Apache foundation is a great fit. Joining
Apache would ensure that tried and true processes and procedures are in
place for the growing number of organizations interested in contributing
to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
PredictionIO was built on top of several Apache projects (HBase, Spark,
Hadoop). We are familiar with the Apache process and believe that the
democratic and meritocratic nature of the foundation aligns with the
project goals.

Initial Goals

The initial milestones will be to move the existing codebase to Apache and
integrate with the Apache development process. Once this is accomplished,
we plan for incremental development and releases that follow the Apache
guidelines, as well as growing our developer and user communities.

Current Status

PredictionIO has undergone nine minor releases and many patches.
PredictionIO is being used in production by Salesforce.com as well as many
other organizations and apps. The PredictionIO codebase is currently
hosted at GitHub, which will form the basis of the Apache git repository.

Meritocracy

We plan to invest in supporting a meritocracy. We will discuss the
requirements in an open forum. We intend to invite additional developers
to participate. We will encourage and monitor community participation so
that privileges can be extended to those that contribute.

Community

Acceptance into the Apache foundation would bolster the already strong
user and developer community around PredictionIO. That community includes
many contributors from various other companies, and an active mailing list
composed of hundreds of users.

Core Developers

The core developers of our project are listed in our contributors and
initial PPMC below. Though many are employed at Salesforce.com, there are
also engineers from ActionML, and independent developers.

Alignment

The ASF is the natural choice to host the PredictionIO project as its goal
is democratizing Machine Learning by making it more easily accessible to
every user/developer. PredictionIO is built on top of several top level
Apache projects as outlined above.

Known Risks

Orphaned Products

PredictionIO has a solid and growing community. It is deployed on
production environments by companies of all sizes to run various kinds of
predictive engines.

In addition to the community contribution to PredictionIO framework, the
community is also actively contributing new engines 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Alexander Bezzubov]

+1 (non-binding) great to see it coming to ASF


On Tue, May 24, 2016 at 2:20 PM, moon soo Lee  wrote:

> +1 (non-binding)
>
> On Mon, May 23, 2016 at 3:23 PM Andrew Purtell 
> wrote:
>
> > Since discussion on the matter of PredictionIO has died down, I would
> like
> > to call a VOTE
> > on accepting PredictionIO into the Apache Incubator.
> >
> > Proposal: https://wiki.apache.org/incubator/PredictionIO
> >
> > ​[ ] +1 Accept PredictionIO into the Apache Incubator
> > [ ] +0 Abstain
> > [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> >
> > This vote will be open for at least 72 hours.
> >
> > My vote is +1 (binding)
> >
> > --
> >
>

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[moon soo Lee]

+1 (non-binding)

On Mon, May 23, 2016 at 3:23 PM Andrew Purtell  wrote:

> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>

RE: [VOTE] Accept PredictionIO into the Apache Incubator

[Priyank Ashok Rastogi]

+1 Accept PredictionIO into the Apache Incubator

-Original Message-
From: Andrew Purtell [mailto:apurt...@apache.org] 
Sent: 24 May 2016 03:52
To: general@incubator.apache.org
Subject: [VOTE] Accept PredictionIO into the Apache Incubator

Since discussion on the matter of PredictionIO has died down, I would like to 
call a VOTE on accepting PredictionIO into the Apache Incubator.

Proposal: https://wiki.apache.org/incubator/PredictionIO

​[ ] +1 Accept PredictionIO into the Apache Incubator [ ] +0 Abstain [ ] -1 Do 
not accept PredictionIO into the Apache Incubator, because ...

This vote will be open for at least 72 hours.

My vote is +1 (binding)

--

PredictionIO Proposal

Abstract

PredictionIO is an open source Machine Learning Server built on top of 
state-of-the-art open source stack, that enables developers to manage and 
deploy production-ready predictive services for various kinds of machine 
learning tasks.

Proposal

The PredictionIO platform consists of the following components:

   * PredictionIO framework - provides the machine learning stack for
 building, evaluating and deploying engines with machine learning
 algorithms. It uses Apache Spark for processing.

   * Event Server - the machine learning analytics layer for unifying events
 from multiple platforms. It can use Apache HBase or any JDBC backends
 as its data store.

The PredictionIO community also maintains a Template Gallery, a place to 
publish and download (free or proprietary) engine templates for different types 
of machine learning applications, and is a complemental part of the project. At 
this point we exclude the Template Gallery from the proposal, as it has a 
separate set of contributors and we’re not familiar with an Apache approved 
mechanism to maintain such a gallery.

Background

PredictionIO was started with a mission to democratize and bring machine 
learning to the masses.

Machine learning has traditionally been a luxury for big companies like Google, 
Facebook, and Netflix. There are ML libraries and tools lying around the 
internet but the effort of putting them all together as a production-ready 
infrastructure is a very resource-intensive task that is remotely reachable by 
individuals or small businesses.

PredictionIO is a production-ready, full stack machine learning system that 
allows organizations of any scale to quickly deploy machine learning 
capabilities. It comes with official and community-contributed machine learning 
engine templates that are easy to customize.

Rationale

As usage and number of contributors to PredictionIO has grown bigger and more 
diverse, we have sought for an independent framework for the project to keep 
thriving. We believe the Apache foundation is a great fit. Joining Apache would 
ensure that tried and true processes and procedures are in place for the 
growing number of organizations interested in contributing to PredictionIO. 
PredictionIO is also a good fit for the Apache foundation.
PredictionIO was built on top of several Apache projects (HBase, Spark, 
Hadoop). We are familiar with the Apache process and believe that the 
democratic and meritocratic nature of the foundation aligns with the project 
goals.

Initial Goals

The initial milestones will be to move the existing codebase to Apache and 
integrate with the Apache development process. Once this is accomplished, we 
plan for incremental development and releases that follow the Apache 
guidelines, as well as growing our developer and user communities.

Current Status

PredictionIO has undergone nine minor releases and many patches.
PredictionIO is being used in production by Salesforce.com as well as many 
other organizations and apps. The PredictionIO codebase is currently hosted at 
GitHub, which will form the basis of the Apache git repository.

Meritocracy

We plan to invest in supporting a meritocracy. We will discuss the requirements 
in an open forum. We intend to invite additional developers to participate. We 
will encourage and monitor community participation so that privileges can be 
extended to those that contribute.

Community

Acceptance into the Apache foundation would bolster the already strong user and 
developer community around PredictionIO. That community includes many 
contributors from various other companies, and an active mailing list composed 
of hundreds of users.

Core Developers

The core developers of our project are listed in our contributors and initial 
PPMC below. Though many are employed at Salesforce.com, there are also 
engineers from ActionML, and independent developers.

Alignment

The ASF is the natural choice to host the PredictionIO project as its goal is 
democratizing Machine Learning by making it more easily accessible to every 
user/developer. PredictionIO is built on top of several top level Apache 
projects as outlined above.

Known Risks

Orphaned Products

PredictionIO has a solid and growing community. It is deployed on production

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Drew Farris]

+1 (binding)

On Mon, May 23, 2016, 6:23 PM Andrew Purtell  wrote:

> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>
> PredictionIO Proposal
>
> Abstract
>
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
>
> Proposal
>
> The PredictionIO platform consists of the following components:
>
>* PredictionIO framework - provides the machine learning stack for
>  building, evaluating and deploying engines with machine learning
>  algorithms. It uses Apache Spark for processing.
>
>* Event Server - the machine learning analytics layer for unifying
> events
>  from multiple platforms. It can use Apache HBase or any JDBC backends
>  as its data store.
>
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
>
> Background
>
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
>
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
>
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
>
> Rationale
>
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
>
> Initial Goals
>
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
>
> Current Status
>
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
>
> Meritocracy
>
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
>
> Community
>
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
>
> Core Developers
>
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
>
> Alignment
>
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
>
> Known Risks
>
> Orphaned Products
>
> PredictionIO has a solid and growing community. It is deployed on
> 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Felix Cheung]

+1 (non-binding)

On Mon, May 23, 2016 at 5:46 PM Henry Saputra 
wrote:

> +1 (binding)
>
> On Mon, May 23, 2016 at 4:46 PM, Ted Dunning 
> wrote:
>
> > +1 (binding)
> >
> >
> >
> > On Mon, May 23, 2016 at 7:31 PM, Debo Dutta (dedutta)  >
> > wrote:
> >
> > > +1
> > >
> > >
> > >
> > >
> > > On 5/23/16, 3:22 PM, "Andrew Purtell"  wrote:
> > >
> > > >Since discussion on the matter of PredictionIO has died down, I would
> > like
> > > >to call a VOTE
> > > >on accepting PredictionIO into the Apache Incubator.
> > > >
> > > >Proposal: https://wiki.apache.org/incubator/PredictionIO
> > > >
> > > >​[ ] +1 Accept PredictionIO into the Apache Incubator
> > > >[ ] +0 Abstain
> > > >[ ] -1 Do not accept PredictionIO into the Apache Incubator, because
> ...
> > > >
> > > >This vote will be open for at least 72 hours.
> > > >
> > > >My vote is +1 (binding)
> > > >
> > > >--
> > > >
> > > >PredictionIO Proposal
> > > >
> > > >Abstract
> > > >
> > > >PredictionIO is an open source Machine Learning Server built on top of
> > > >state-of-the-art open source stack, that enables developers to manage
> > and
> > > >deploy production-ready predictive services for various kinds of
> machine
> > > >learning tasks.
> > > >
> > > >Proposal
> > > >
> > > >The PredictionIO platform consists of the following components:
> > > >
> > > >   * PredictionIO framework - provides the machine learning stack for
> > > > building, evaluating and deploying engines with machine learning
> > > > algorithms. It uses Apache Spark for processing.
> > > >
> > > >   * Event Server - the machine learning analytics layer for unifying
> > > events
> > > > from multiple platforms. It can use Apache HBase or any JDBC
> > backends
> > > > as its data store.
> > > >
> > > >The PredictionIO community also maintains a Template Gallery, a place
> to
> > > >publish and download (free or proprietary) engine templates for
> > different
> > > >types of machine learning applications, and is a complemental part of
> > the
> > > >project. At this point we exclude the Template Gallery from the
> > proposal,
> > > >as it has a separate set of contributors and we’re not familiar with
> an
> > > >Apache approved mechanism to maintain such a gallery.
> > > >
> > > >Background
> > > >
> > > >PredictionIO was started with a mission to democratize and bring
> machine
> > > >learning to the masses.
> > > >
> > > >Machine learning has traditionally been a luxury for big companies
> like
> > > >Google, Facebook, and Netflix. There are ML libraries and tools lying
> > > >around the internet but the effort of putting them all together as a
> > > >production-ready infrastructure is a very resource-intensive task that
> > is
> > > >remotely reachable by individuals or small businesses.
> > > >
> > > >PredictionIO is a production-ready, full stack machine learning system
> > > that
> > > >allows organizations of any scale to quickly deploy machine learning
> > > >capabilities. It comes with official and community-contributed machine
> > > >learning engine templates that are easy to customize.
> > > >
> > > >Rationale
> > > >
> > > >As usage and number of contributors to PredictionIO has grown bigger
> and
> > > >more diverse, we have sought for an independent framework for the
> > project
> > > >to keep thriving. We believe the Apache foundation is a great fit.
> > Joining
> > > >Apache would ensure that tried and true processes and procedures are
> in
> > > >place for the growing number of organizations interested in
> contributing
> > > >to PredictionIO. PredictionIO is also a good fit for the Apache
> > > foundation.
> > > >PredictionIO was built on top of several Apache projects (HBase,
> Spark,
> > > >Hadoop). We are familiar with the Apache process and believe that the
> > > >democratic and meritocratic nature of the foundation aligns with the
> > > >project goals.
> > > >
> > > >Initial Goals
> > > >
> > > >The initial milestones will be to move the existing codebase to Apache
> > and
> > > >integrate with the Apache development process. Once this is
> > accomplished,
> > > >we plan for incremental development and releases that follow the
> Apache
> > > >guidelines, as well as growing our developer and user communities.
> > > >
> > > >Current Status
> > > >
> > > >PredictionIO has undergone nine minor releases and many patches.
> > > >PredictionIO is being used in production by Salesforce.com as well as
> > many
> > > >other organizations and apps. The PredictionIO codebase is currently
> > > >hosted at GitHub, which will form the basis of the Apache git
> > repository.
> > > >
> > > >Meritocracy
> > > >
> > > >We plan to invest in supporting a meritocracy. We will discuss the
> > > >requirements in an open forum. We intend to invite additional
> developers
> > > >to participate. We will encourage and monitor community participation
> so
> > > >that privileges can be 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Henry Saputra]

+1 (binding)

On Mon, May 23, 2016 at 4:46 PM, Ted Dunning  wrote:

> +1 (binding)
>
>
>
> On Mon, May 23, 2016 at 7:31 PM, Debo Dutta (dedutta) 
> wrote:
>
> > +1
> >
> >
> >
> >
> > On 5/23/16, 3:22 PM, "Andrew Purtell"  wrote:
> >
> > >Since discussion on the matter of PredictionIO has died down, I would
> like
> > >to call a VOTE
> > >on accepting PredictionIO into the Apache Incubator.
> > >
> > >Proposal: https://wiki.apache.org/incubator/PredictionIO
> > >
> > >​[ ] +1 Accept PredictionIO into the Apache Incubator
> > >[ ] +0 Abstain
> > >[ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> > >
> > >This vote will be open for at least 72 hours.
> > >
> > >My vote is +1 (binding)
> > >
> > >--
> > >
> > >PredictionIO Proposal
> > >
> > >Abstract
> > >
> > >PredictionIO is an open source Machine Learning Server built on top of
> > >state-of-the-art open source stack, that enables developers to manage
> and
> > >deploy production-ready predictive services for various kinds of machine
> > >learning tasks.
> > >
> > >Proposal
> > >
> > >The PredictionIO platform consists of the following components:
> > >
> > >   * PredictionIO framework - provides the machine learning stack for
> > > building, evaluating and deploying engines with machine learning
> > > algorithms. It uses Apache Spark for processing.
> > >
> > >   * Event Server - the machine learning analytics layer for unifying
> > events
> > > from multiple platforms. It can use Apache HBase or any JDBC
> backends
> > > as its data store.
> > >
> > >The PredictionIO community also maintains a Template Gallery, a place to
> > >publish and download (free or proprietary) engine templates for
> different
> > >types of machine learning applications, and is a complemental part of
> the
> > >project. At this point we exclude the Template Gallery from the
> proposal,
> > >as it has a separate set of contributors and we’re not familiar with an
> > >Apache approved mechanism to maintain such a gallery.
> > >
> > >Background
> > >
> > >PredictionIO was started with a mission to democratize and bring machine
> > >learning to the masses.
> > >
> > >Machine learning has traditionally been a luxury for big companies like
> > >Google, Facebook, and Netflix. There are ML libraries and tools lying
> > >around the internet but the effort of putting them all together as a
> > >production-ready infrastructure is a very resource-intensive task that
> is
> > >remotely reachable by individuals or small businesses.
> > >
> > >PredictionIO is a production-ready, full stack machine learning system
> > that
> > >allows organizations of any scale to quickly deploy machine learning
> > >capabilities. It comes with official and community-contributed machine
> > >learning engine templates that are easy to customize.
> > >
> > >Rationale
> > >
> > >As usage and number of contributors to PredictionIO has grown bigger and
> > >more diverse, we have sought for an independent framework for the
> project
> > >to keep thriving. We believe the Apache foundation is a great fit.
> Joining
> > >Apache would ensure that tried and true processes and procedures are in
> > >place for the growing number of organizations interested in contributing
> > >to PredictionIO. PredictionIO is also a good fit for the Apache
> > foundation.
> > >PredictionIO was built on top of several Apache projects (HBase, Spark,
> > >Hadoop). We are familiar with the Apache process and believe that the
> > >democratic and meritocratic nature of the foundation aligns with the
> > >project goals.
> > >
> > >Initial Goals
> > >
> > >The initial milestones will be to move the existing codebase to Apache
> and
> > >integrate with the Apache development process. Once this is
> accomplished,
> > >we plan for incremental development and releases that follow the Apache
> > >guidelines, as well as growing our developer and user communities.
> > >
> > >Current Status
> > >
> > >PredictionIO has undergone nine minor releases and many patches.
> > >PredictionIO is being used in production by Salesforce.com as well as
> many
> > >other organizations and apps. The PredictionIO codebase is currently
> > >hosted at GitHub, which will form the basis of the Apache git
> repository.
> > >
> > >Meritocracy
> > >
> > >We plan to invest in supporting a meritocracy. We will discuss the
> > >requirements in an open forum. We intend to invite additional developers
> > >to participate. We will encourage and monitor community participation so
> > >that privileges can be extended to those that contribute.
> > >
> > >Community
> > >
> > >Acceptance into the Apache foundation would bolster the already strong
> > >user and developer community around PredictionIO. That community
> includes
> > >many contributors from various other companies, and an active mailing
> list
> > >composed of hundreds of users.
> > >
> > >Core Developers
> > >
> > >The core 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Ted Dunning]

+1 (binding)



On Mon, May 23, 2016 at 7:31 PM, Debo Dutta (dedutta) 
wrote:

> +1
>
>
>
>
> On 5/23/16, 3:22 PM, "Andrew Purtell"  wrote:
>
> >Since discussion on the matter of PredictionIO has died down, I would like
> >to call a VOTE
> >on accepting PredictionIO into the Apache Incubator.
> >
> >Proposal: https://wiki.apache.org/incubator/PredictionIO
> >
> >​[ ] +1 Accept PredictionIO into the Apache Incubator
> >[ ] +0 Abstain
> >[ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> >
> >This vote will be open for at least 72 hours.
> >
> >My vote is +1 (binding)
> >
> >--
> >
> >PredictionIO Proposal
> >
> >Abstract
> >
> >PredictionIO is an open source Machine Learning Server built on top of
> >state-of-the-art open source stack, that enables developers to manage and
> >deploy production-ready predictive services for various kinds of machine
> >learning tasks.
> >
> >Proposal
> >
> >The PredictionIO platform consists of the following components:
> >
> >   * PredictionIO framework - provides the machine learning stack for
> > building, evaluating and deploying engines with machine learning
> > algorithms. It uses Apache Spark for processing.
> >
> >   * Event Server - the machine learning analytics layer for unifying
> events
> > from multiple platforms. It can use Apache HBase or any JDBC backends
> > as its data store.
> >
> >The PredictionIO community also maintains a Template Gallery, a place to
> >publish and download (free or proprietary) engine templates for different
> >types of machine learning applications, and is a complemental part of the
> >project. At this point we exclude the Template Gallery from the proposal,
> >as it has a separate set of contributors and we’re not familiar with an
> >Apache approved mechanism to maintain such a gallery.
> >
> >Background
> >
> >PredictionIO was started with a mission to democratize and bring machine
> >learning to the masses.
> >
> >Machine learning has traditionally been a luxury for big companies like
> >Google, Facebook, and Netflix. There are ML libraries and tools lying
> >around the internet but the effort of putting them all together as a
> >production-ready infrastructure is a very resource-intensive task that is
> >remotely reachable by individuals or small businesses.
> >
> >PredictionIO is a production-ready, full stack machine learning system
> that
> >allows organizations of any scale to quickly deploy machine learning
> >capabilities. It comes with official and community-contributed machine
> >learning engine templates that are easy to customize.
> >
> >Rationale
> >
> >As usage and number of contributors to PredictionIO has grown bigger and
> >more diverse, we have sought for an independent framework for the project
> >to keep thriving. We believe the Apache foundation is a great fit. Joining
> >Apache would ensure that tried and true processes and procedures are in
> >place for the growing number of organizations interested in contributing
> >to PredictionIO. PredictionIO is also a good fit for the Apache
> foundation.
> >PredictionIO was built on top of several Apache projects (HBase, Spark,
> >Hadoop). We are familiar with the Apache process and believe that the
> >democratic and meritocratic nature of the foundation aligns with the
> >project goals.
> >
> >Initial Goals
> >
> >The initial milestones will be to move the existing codebase to Apache and
> >integrate with the Apache development process. Once this is accomplished,
> >we plan for incremental development and releases that follow the Apache
> >guidelines, as well as growing our developer and user communities.
> >
> >Current Status
> >
> >PredictionIO has undergone nine minor releases and many patches.
> >PredictionIO is being used in production by Salesforce.com as well as many
> >other organizations and apps. The PredictionIO codebase is currently
> >hosted at GitHub, which will form the basis of the Apache git repository.
> >
> >Meritocracy
> >
> >We plan to invest in supporting a meritocracy. We will discuss the
> >requirements in an open forum. We intend to invite additional developers
> >to participate. We will encourage and monitor community participation so
> >that privileges can be extended to those that contribute.
> >
> >Community
> >
> >Acceptance into the Apache foundation would bolster the already strong
> >user and developer community around PredictionIO. That community includes
> >many contributors from various other companies, and an active mailing list
> >composed of hundreds of users.
> >
> >Core Developers
> >
> >The core developers of our project are listed in our contributors and
> >initial PPMC below. Though many are employed at Salesforce.com, there are
> >also engineers from ActionML, and independent developers.
> >
> >Alignment
> >
> >The ASF is the natural choice to host the PredictionIO project as its goal
> >is democratizing Machine Learning by making it more easily 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Debo Dutta (dedutta)]

+1




On 5/23/16, 3:22 PM, "Andrew Purtell"  wrote:

>Since discussion on the matter of PredictionIO has died down, I would like
>to call a VOTE
>on accepting PredictionIO into the Apache Incubator.
>
>Proposal: https://wiki.apache.org/incubator/PredictionIO
>
>​[ ] +1 Accept PredictionIO into the Apache Incubator
>[ ] +0 Abstain
>[ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
>This vote will be open for at least 72 hours.
>
>My vote is +1 (binding)
>
>--
>
>PredictionIO Proposal
>
>Abstract
>
>PredictionIO is an open source Machine Learning Server built on top of
>state-of-the-art open source stack, that enables developers to manage and
>deploy production-ready predictive services for various kinds of machine
>learning tasks.
>
>Proposal
>
>The PredictionIO platform consists of the following components:
>
>   * PredictionIO framework - provides the machine learning stack for
> building, evaluating and deploying engines with machine learning
> algorithms. It uses Apache Spark for processing.
>
>   * Event Server - the machine learning analytics layer for unifying events
> from multiple platforms. It can use Apache HBase or any JDBC backends
> as its data store.
>
>The PredictionIO community also maintains a Template Gallery, a place to
>publish and download (free or proprietary) engine templates for different
>types of machine learning applications, and is a complemental part of the
>project. At this point we exclude the Template Gallery from the proposal,
>as it has a separate set of contributors and we’re not familiar with an
>Apache approved mechanism to maintain such a gallery.
>
>Background
>
>PredictionIO was started with a mission to democratize and bring machine
>learning to the masses.
>
>Machine learning has traditionally been a luxury for big companies like
>Google, Facebook, and Netflix. There are ML libraries and tools lying
>around the internet but the effort of putting them all together as a
>production-ready infrastructure is a very resource-intensive task that is
>remotely reachable by individuals or small businesses.
>
>PredictionIO is a production-ready, full stack machine learning system that
>allows organizations of any scale to quickly deploy machine learning
>capabilities. It comes with official and community-contributed machine
>learning engine templates that are easy to customize.
>
>Rationale
>
>As usage and number of contributors to PredictionIO has grown bigger and
>more diverse, we have sought for an independent framework for the project
>to keep thriving. We believe the Apache foundation is a great fit. Joining
>Apache would ensure that tried and true processes and procedures are in
>place for the growing number of organizations interested in contributing
>to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
>PredictionIO was built on top of several Apache projects (HBase, Spark,
>Hadoop). We are familiar with the Apache process and believe that the
>democratic and meritocratic nature of the foundation aligns with the
>project goals.
>
>Initial Goals
>
>The initial milestones will be to move the existing codebase to Apache and
>integrate with the Apache development process. Once this is accomplished,
>we plan for incremental development and releases that follow the Apache
>guidelines, as well as growing our developer and user communities.
>
>Current Status
>
>PredictionIO has undergone nine minor releases and many patches.
>PredictionIO is being used in production by Salesforce.com as well as many
>other organizations and apps. The PredictionIO codebase is currently
>hosted at GitHub, which will form the basis of the Apache git repository.
>
>Meritocracy
>
>We plan to invest in supporting a meritocracy. We will discuss the
>requirements in an open forum. We intend to invite additional developers
>to participate. We will encourage and monitor community participation so
>that privileges can be extended to those that contribute.
>
>Community
>
>Acceptance into the Apache foundation would bolster the already strong
>user and developer community around PredictionIO. That community includes
>many contributors from various other companies, and an active mailing list
>composed of hundreds of users.
>
>Core Developers
>
>The core developers of our project are listed in our contributors and
>initial PPMC below. Though many are employed at Salesforce.com, there are
>also engineers from ActionML, and independent developers.
>
>Alignment
>
>The ASF is the natural choice to host the PredictionIO project as its goal
>is democratizing Machine Learning by making it more easily accessible to
>every user/developer. PredictionIO is built on top of several top level
>Apache projects as outlined above.
>
>Known Risks
>
>Orphaned Products
>
>PredictionIO has a solid and growing community. It is deployed on
>production environments by companies of all sizes to run various kinds of
>predictive engines.
>
>In 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Roman Shaposhnik]

On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell  wrote:
> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> [ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...

+1 (binding)

Thanks,
Roman.

-
To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org
For additional commands, e-mail: general-h...@incubator.apache.org

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Chris Nauroth]

+1 (binding)

--Chris Nauroth




On 5/23/16, 3:22 PM, "Andrew Purtell"  wrote:

>Since discussion on the matter of PredictionIO has died down, I would like
>to call a VOTE
>on accepting PredictionIO into the Apache Incubator.
>
>Proposal: https://wiki.apache.org/incubator/PredictionIO
>
>​[ ] +1 Accept PredictionIO into the Apache Incubator
>[ ] +0 Abstain
>[ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
>This vote will be open for at least 72 hours.
>
>My vote is +1 (binding)
>
>--
>
>PredictionIO Proposal
>
>Abstract
>
>PredictionIO is an open source Machine Learning Server built on top of
>state-of-the-art open source stack, that enables developers to manage and
>deploy production-ready predictive services for various kinds of machine
>learning tasks.
>
>Proposal
>
>The PredictionIO platform consists of the following components:
>
>   * PredictionIO framework - provides the machine learning stack for
> building, evaluating and deploying engines with machine learning
> algorithms. It uses Apache Spark for processing.
>
>   * Event Server - the machine learning analytics layer for unifying
>events
> from multiple platforms. It can use Apache HBase or any JDBC backends
> as its data store.
>
>The PredictionIO community also maintains a Template Gallery, a place to
>publish and download (free or proprietary) engine templates for different
>types of machine learning applications, and is a complemental part of the
>project. At this point we exclude the Template Gallery from the proposal,
>as it has a separate set of contributors and we’re not familiar with an
>Apache approved mechanism to maintain such a gallery.
>
>Background
>
>PredictionIO was started with a mission to democratize and bring machine
>learning to the masses.
>
>Machine learning has traditionally been a luxury for big companies like
>Google, Facebook, and Netflix. There are ML libraries and tools lying
>around the internet but the effort of putting them all together as a
>production-ready infrastructure is a very resource-intensive task that is
>remotely reachable by individuals or small businesses.
>
>PredictionIO is a production-ready, full stack machine learning system
>that
>allows organizations of any scale to quickly deploy machine learning
>capabilities. It comes with official and community-contributed machine
>learning engine templates that are easy to customize.
>
>Rationale
>
>As usage and number of contributors to PredictionIO has grown bigger and
>more diverse, we have sought for an independent framework for the project
>to keep thriving. We believe the Apache foundation is a great fit. Joining
>Apache would ensure that tried and true processes and procedures are in
>place for the growing number of organizations interested in contributing
>to PredictionIO. PredictionIO is also a good fit for the Apache
>foundation.
>PredictionIO was built on top of several Apache projects (HBase, Spark,
>Hadoop). We are familiar with the Apache process and believe that the
>democratic and meritocratic nature of the foundation aligns with the
>project goals.
>
>Initial Goals
>
>The initial milestones will be to move the existing codebase to Apache and
>integrate with the Apache development process. Once this is accomplished,
>we plan for incremental development and releases that follow the Apache
>guidelines, as well as growing our developer and user communities.
>
>Current Status
>
>PredictionIO has undergone nine minor releases and many patches.
>PredictionIO is being used in production by Salesforce.com as well as many
>other organizations and apps. The PredictionIO codebase is currently
>hosted at GitHub, which will form the basis of the Apache git repository.
>
>Meritocracy
>
>We plan to invest in supporting a meritocracy. We will discuss the
>requirements in an open forum. We intend to invite additional developers
>to participate. We will encourage and monitor community participation so
>that privileges can be extended to those that contribute.
>
>Community
>
>Acceptance into the Apache foundation would bolster the already strong
>user and developer community around PredictionIO. That community includes
>many contributors from various other companies, and an active mailing list
>composed of hundreds of users.
>
>Core Developers
>
>The core developers of our project are listed in our contributors and
>initial PPMC below. Though many are employed at Salesforce.com, there are
>also engineers from ActionML, and independent developers.
>
>Alignment
>
>The ASF is the natural choice to host the PredictionIO project as its goal
>is democratizing Machine Learning by making it more easily accessible to
>every user/developer. PredictionIO is built on top of several top level
>Apache projects as outlined above.
>
>Known Risks
>
>Orphaned Products
>
>PredictionIO has a solid and growing community. It is deployed on
>production environments by companies of all sizes to run various kinds of

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Ashish]

+1 (non-binding)

On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell  wrote:
> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> [ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>
> PredictionIO Proposal
>
> Abstract
>
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
>
> Proposal
>
> The PredictionIO platform consists of the following components:
>
>* PredictionIO framework - provides the machine learning stack for
>  building, evaluating and deploying engines with machine learning
>  algorithms. It uses Apache Spark for processing.
>
>* Event Server - the machine learning analytics layer for unifying events
>  from multiple platforms. It can use Apache HBase or any JDBC backends
>  as its data store.
>
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
>
> Background
>
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
>
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
>
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
>
> Rationale
>
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
>
> Initial Goals
>
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
>
> Current Status
>
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
>
> Meritocracy
>
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
>
> Community
>
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
>
> Core Developers
>
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
>
> Alignment
>
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
>
> Known Risks
>
> Orphaned Products
>
> PredictionIO has a solid and growing community. It is deployed on
> 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Suneel Marthi]

+1 (binding)

On Mon, May 23, 2016 at 6:32 PM, Luciano Resende 
wrote:

> +1 (binding)
>
> On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell 
> wrote:
>
> > Since discussion on the matter of PredictionIO has died down, I would
> like
> > to call a VOTE
> > on accepting PredictionIO into the Apache Incubator.
> >
> > Proposal: https://wiki.apache.org/incubator/PredictionIO
> >
> > ​[ ] +1 Accept PredictionIO into the Apache Incubator
> > [ ] +0 Abstain
> > [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> >
> > This vote will be open for at least 72 hours.
> >
> > My vote is +1 (binding)
> >
> > --
> >
> > PredictionIO Proposal
> >
> > Abstract
> >
> > PredictionIO is an open source Machine Learning Server built on top of
> > state-of-the-art open source stack, that enables developers to manage and
> > deploy production-ready predictive services for various kinds of machine
> > learning tasks.
> >
> > Proposal
> >
> > The PredictionIO platform consists of the following components:
> >
> >* PredictionIO framework - provides the machine learning stack for
> >  building, evaluating and deploying engines with machine learning
> >  algorithms. It uses Apache Spark for processing.
> >
> >* Event Server - the machine learning analytics layer for unifying
> > events
> >  from multiple platforms. It can use Apache HBase or any JDBC
> backends
> >  as its data store.
> >
> > The PredictionIO community also maintains a Template Gallery, a place to
> > publish and download (free or proprietary) engine templates for different
> > types of machine learning applications, and is a complemental part of the
> > project. At this point we exclude the Template Gallery from the proposal,
> > as it has a separate set of contributors and we’re not familiar with an
> > Apache approved mechanism to maintain such a gallery.
> >
> > Background
> >
> > PredictionIO was started with a mission to democratize and bring machine
> > learning to the masses.
> >
> > Machine learning has traditionally been a luxury for big companies like
> > Google, Facebook, and Netflix. There are ML libraries and tools lying
> > around the internet but the effort of putting them all together as a
> > production-ready infrastructure is a very resource-intensive task that is
> > remotely reachable by individuals or small businesses.
> >
> > PredictionIO is a production-ready, full stack machine learning system
> that
> > allows organizations of any scale to quickly deploy machine learning
> > capabilities. It comes with official and community-contributed machine
> > learning engine templates that are easy to customize.
> >
> > Rationale
> >
> > As usage and number of contributors to PredictionIO has grown bigger and
> > more diverse, we have sought for an independent framework for the project
> > to keep thriving. We believe the Apache foundation is a great fit.
> Joining
> > Apache would ensure that tried and true processes and procedures are in
> > place for the growing number of organizations interested in contributing
> > to PredictionIO. PredictionIO is also a good fit for the Apache
> foundation.
> > PredictionIO was built on top of several Apache projects (HBase, Spark,
> > Hadoop). We are familiar with the Apache process and believe that the
> > democratic and meritocratic nature of the foundation aligns with the
> > project goals.
> >
> > Initial Goals
> >
> > The initial milestones will be to move the existing codebase to Apache
> and
> > integrate with the Apache development process. Once this is accomplished,
> > we plan for incremental development and releases that follow the Apache
> > guidelines, as well as growing our developer and user communities.
> >
> > Current Status
> >
> > PredictionIO has undergone nine minor releases and many patches.
> > PredictionIO is being used in production by Salesforce.com as well as
> many
> > other organizations and apps. The PredictionIO codebase is currently
> > hosted at GitHub, which will form the basis of the Apache git repository.
> >
> > Meritocracy
> >
> > We plan to invest in supporting a meritocracy. We will discuss the
> > requirements in an open forum. We intend to invite additional developers
> > to participate. We will encourage and monitor community participation so
> > that privileges can be extended to those that contribute.
> >
> > Community
> >
> > Acceptance into the Apache foundation would bolster the already strong
> > user and developer community around PredictionIO. That community includes
> > many contributors from various other companies, and an active mailing
> list
> > composed of hundreds of users.
> >
> > Core Developers
> >
> > The core developers of our project are listed in our contributors and
> > initial PPMC below. Though many are employed at Salesforce.com, there are
> > also engineers from ActionML, and independent developers.
> >
> > Alignment
> >
> > The ASF is the natural choice 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[Luciano Resende]

+1 (binding)

On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell  wrote:

> Since discussion on the matter of PredictionIO has died down, I would like
> to call a VOTE
> on accepting PredictionIO into the Apache Incubator.
>
> Proposal: https://wiki.apache.org/incubator/PredictionIO
>
> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> [ ] +0 Abstain
> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
>
> This vote will be open for at least 72 hours.
>
> My vote is +1 (binding)
>
> --
>
> PredictionIO Proposal
>
> Abstract
>
> PredictionIO is an open source Machine Learning Server built on top of
> state-of-the-art open source stack, that enables developers to manage and
> deploy production-ready predictive services for various kinds of machine
> learning tasks.
>
> Proposal
>
> The PredictionIO platform consists of the following components:
>
>* PredictionIO framework - provides the machine learning stack for
>  building, evaluating and deploying engines with machine learning
>  algorithms. It uses Apache Spark for processing.
>
>* Event Server - the machine learning analytics layer for unifying
> events
>  from multiple platforms. It can use Apache HBase or any JDBC backends
>  as its data store.
>
> The PredictionIO community also maintains a Template Gallery, a place to
> publish and download (free or proprietary) engine templates for different
> types of machine learning applications, and is a complemental part of the
> project. At this point we exclude the Template Gallery from the proposal,
> as it has a separate set of contributors and we’re not familiar with an
> Apache approved mechanism to maintain such a gallery.
>
> Background
>
> PredictionIO was started with a mission to democratize and bring machine
> learning to the masses.
>
> Machine learning has traditionally been a luxury for big companies like
> Google, Facebook, and Netflix. There are ML libraries and tools lying
> around the internet but the effort of putting them all together as a
> production-ready infrastructure is a very resource-intensive task that is
> remotely reachable by individuals or small businesses.
>
> PredictionIO is a production-ready, full stack machine learning system that
> allows organizations of any scale to quickly deploy machine learning
> capabilities. It comes with official and community-contributed machine
> learning engine templates that are easy to customize.
>
> Rationale
>
> As usage and number of contributors to PredictionIO has grown bigger and
> more diverse, we have sought for an independent framework for the project
> to keep thriving. We believe the Apache foundation is a great fit. Joining
> Apache would ensure that tried and true processes and procedures are in
> place for the growing number of organizations interested in contributing
> to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
> PredictionIO was built on top of several Apache projects (HBase, Spark,
> Hadoop). We are familiar with the Apache process and believe that the
> democratic and meritocratic nature of the foundation aligns with the
> project goals.
>
> Initial Goals
>
> The initial milestones will be to move the existing codebase to Apache and
> integrate with the Apache development process. Once this is accomplished,
> we plan for incremental development and releases that follow the Apache
> guidelines, as well as growing our developer and user communities.
>
> Current Status
>
> PredictionIO has undergone nine minor releases and many patches.
> PredictionIO is being used in production by Salesforce.com as well as many
> other organizations and apps. The PredictionIO codebase is currently
> hosted at GitHub, which will form the basis of the Apache git repository.
>
> Meritocracy
>
> We plan to invest in supporting a meritocracy. We will discuss the
> requirements in an open forum. We intend to invite additional developers
> to participate. We will encourage and monitor community participation so
> that privileges can be extended to those that contribute.
>
> Community
>
> Acceptance into the Apache foundation would bolster the already strong
> user and developer community around PredictionIO. That community includes
> many contributors from various other companies, and an active mailing list
> composed of hundreds of users.
>
> Core Developers
>
> The core developers of our project are listed in our contributors and
> initial PPMC below. Though many are employed at Salesforce.com, there are
> also engineers from ActionML, and independent developers.
>
> Alignment
>
> The ASF is the natural choice to host the PredictionIO project as its goal
> is democratizing Machine Learning by making it more easily accessible to
> every user/developer. PredictionIO is built on top of several top level
> Apache projects as outlined above.
>
> Known Risks
>
> Orphaned Products
>
> PredictionIO has a solid and growing community. It is deployed on
> 

Re: [VOTE] Accept PredictionIO into the Apache Incubator

[James Taylor]

+1 (binding)

On Mon, May 23, 2016 at 3:32 PM, Luciano Resende 
wrote:

> +1 (binding)
>
> On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell 
> wrote:
>
> > Since discussion on the matter of PredictionIO has died down, I would
> like
> > to call a VOTE
> > on accepting PredictionIO into the Apache Incubator.
> >
> > Proposal: https://wiki.apache.org/incubator/PredictionIO
> >
> > ​[ ] +1 Accept PredictionIO into the Apache Incubator
> > [ ] +0 Abstain
> > [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> >
> > This vote will be open for at least 72 hours.
> >
> > My vote is +1 (binding)
> >
> > --
> >
> > PredictionIO Proposal
> >
> > Abstract
> >
> > PredictionIO is an open source Machine Learning Server built on top of
> > state-of-the-art open source stack, that enables developers to manage and
> > deploy production-ready predictive services for various kinds of machine
> > learning tasks.
> >
> > Proposal
> >
> > The PredictionIO platform consists of the following components:
> >
> >* PredictionIO framework - provides the machine learning stack for
> >  building, evaluating and deploying engines with machine learning
> >  algorithms. It uses Apache Spark for processing.
> >
> >* Event Server - the machine learning analytics layer for unifying
> > events
> >  from multiple platforms. It can use Apache HBase or any JDBC
> backends
> >  as its data store.
> >
> > The PredictionIO community also maintains a Template Gallery, a place to
> > publish and download (free or proprietary) engine templates for different
> > types of machine learning applications, and is a complemental part of the
> > project. At this point we exclude the Template Gallery from the proposal,
> > as it has a separate set of contributors and we’re not familiar with an
> > Apache approved mechanism to maintain such a gallery.
> >
> > Background
> >
> > PredictionIO was started with a mission to democratize and bring machine
> > learning to the masses.
> >
> > Machine learning has traditionally been a luxury for big companies like
> > Google, Facebook, and Netflix. There are ML libraries and tools lying
> > around the internet but the effort of putting them all together as a
> > production-ready infrastructure is a very resource-intensive task that is
> > remotely reachable by individuals or small businesses.
> >
> > PredictionIO is a production-ready, full stack machine learning system
> that
> > allows organizations of any scale to quickly deploy machine learning
> > capabilities. It comes with official and community-contributed machine
> > learning engine templates that are easy to customize.
> >
> > Rationale
> >
> > As usage and number of contributors to PredictionIO has grown bigger and
> > more diverse, we have sought for an independent framework for the project
> > to keep thriving. We believe the Apache foundation is a great fit.
> Joining
> > Apache would ensure that tried and true processes and procedures are in
> > place for the growing number of organizations interested in contributing
> > to PredictionIO. PredictionIO is also a good fit for the Apache
> foundation.
> > PredictionIO was built on top of several Apache projects (HBase, Spark,
> > Hadoop). We are familiar with the Apache process and believe that the
> > democratic and meritocratic nature of the foundation aligns with the
> > project goals.
> >
> > Initial Goals
> >
> > The initial milestones will be to move the existing codebase to Apache
> and
> > integrate with the Apache development process. Once this is accomplished,
> > we plan for incremental development and releases that follow the Apache
> > guidelines, as well as growing our developer and user communities.
> >
> > Current Status
> >
> > PredictionIO has undergone nine minor releases and many patches.
> > PredictionIO is being used in production by Salesforce.com as well as
> many
> > other organizations and apps. The PredictionIO codebase is currently
> > hosted at GitHub, which will form the basis of the Apache git repository.
> >
> > Meritocracy
> >
> > We plan to invest in supporting a meritocracy. We will discuss the
> > requirements in an open forum. We intend to invite additional developers
> > to participate. We will encourage and monitor community participation so
> > that privileges can be extended to those that contribute.
> >
> > Community
> >
> > Acceptance into the Apache foundation would bolster the already strong
> > user and developer community around PredictionIO. That community includes
> > many contributors from various other companies, and an active mailing
> list
> > composed of hundreds of users.
> >
> > Core Developers
> >
> > The core developers of our project are listed in our contributors and
> > initial PPMC below. Though many are employed at Salesforce.com, there are
> > also engineers from ActionML, and independent developers.
> >
> > Alignment
> >
> > The ASF is the natural choice 

[VOTE] Accept PredictionIO into the Apache Incubator

[Andrew Purtell]

Since discussion on the matter of PredictionIO has died down, I would like
to call a VOTE
on accepting PredictionIO into the Apache Incubator.

Proposal: https://wiki.apache.org/incubator/PredictionIO

​[ ] +1 Accept PredictionIO into the Apache Incubator
[ ] +0 Abstain
[ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...

This vote will be open for at least 72 hours.

My vote is +1 (binding)

--

PredictionIO Proposal

Abstract

PredictionIO is an open source Machine Learning Server built on top of
state-of-the-art open source stack, that enables developers to manage and
deploy production-ready predictive services for various kinds of machine
learning tasks.

Proposal

The PredictionIO platform consists of the following components:

   * PredictionIO framework - provides the machine learning stack for
 building, evaluating and deploying engines with machine learning
 algorithms. It uses Apache Spark for processing.

   * Event Server - the machine learning analytics layer for unifying events
 from multiple platforms. It can use Apache HBase or any JDBC backends
 as its data store.

The PredictionIO community also maintains a Template Gallery, a place to
publish and download (free or proprietary) engine templates for different
types of machine learning applications, and is a complemental part of the
project. At this point we exclude the Template Gallery from the proposal,
as it has a separate set of contributors and we’re not familiar with an
Apache approved mechanism to maintain such a gallery.

Background

PredictionIO was started with a mission to democratize and bring machine
learning to the masses.

Machine learning has traditionally been a luxury for big companies like
Google, Facebook, and Netflix. There are ML libraries and tools lying
around the internet but the effort of putting them all together as a
production-ready infrastructure is a very resource-intensive task that is
remotely reachable by individuals or small businesses.

PredictionIO is a production-ready, full stack machine learning system that
allows organizations of any scale to quickly deploy machine learning
capabilities. It comes with official and community-contributed machine
learning engine templates that are easy to customize.

Rationale

As usage and number of contributors to PredictionIO has grown bigger and
more diverse, we have sought for an independent framework for the project
to keep thriving. We believe the Apache foundation is a great fit. Joining
Apache would ensure that tried and true processes and procedures are in
place for the growing number of organizations interested in contributing
to PredictionIO. PredictionIO is also a good fit for the Apache foundation.
PredictionIO was built on top of several Apache projects (HBase, Spark,
Hadoop). We are familiar with the Apache process and believe that the
democratic and meritocratic nature of the foundation aligns with the
project goals.

Initial Goals

The initial milestones will be to move the existing codebase to Apache and
integrate with the Apache development process. Once this is accomplished,
we plan for incremental development and releases that follow the Apache
guidelines, as well as growing our developer and user communities.

Current Status

PredictionIO has undergone nine minor releases and many patches.
PredictionIO is being used in production by Salesforce.com as well as many
other organizations and apps. The PredictionIO codebase is currently
hosted at GitHub, which will form the basis of the Apache git repository.

Meritocracy

We plan to invest in supporting a meritocracy. We will discuss the
requirements in an open forum. We intend to invite additional developers
to participate. We will encourage and monitor community participation so
that privileges can be extended to those that contribute.

Community

Acceptance into the Apache foundation would bolster the already strong
user and developer community around PredictionIO. That community includes
many contributors from various other companies, and an active mailing list
composed of hundreds of users.

Core Developers

The core developers of our project are listed in our contributors and
initial PPMC below. Though many are employed at Salesforce.com, there are
also engineers from ActionML, and independent developers.

Alignment

The ASF is the natural choice to host the PredictionIO project as its goal
is democratizing Machine Learning by making it more easily accessible to
every user/developer. PredictionIO is built on top of several top level
Apache projects as outlined above.

Known Risks

Orphaned Products

PredictionIO has a solid and growing community. It is deployed on
production environments by companies of all sizes to run various kinds of
predictive engines.

In addition to the community contribution to PredictionIO framework, the
community is also actively contributing new engines to the Template
Gallery as well as SDKs and documentation for the project.