Good! I agree.
The Apache Marvin-AI platform aims to offer a practical and standardized
solution to help its users to perform data exploration, model development
and application lifecycle management for artificial intelligence tasks,
aiming to offer: scalability, language agnosticism and a
+1
Em sáb., 15 de ago. de 2020 às 08:57, Lucas Bonatto Miguel <
lucasb...@apache.org> escreveu:
> It's good, the only thing I would change would be to mention what sort of
> applications. Although we have AI in the name, one may mistakenly think
> Marvin is intended to serve any type of
It's good, the only thing I would change would be to mention what sort of
applications. Although we have AI in the name, one may mistakenly think
Marvin is intended to serve any type of application.
Best
On Fri, Aug 14, 2020 at 11:37 AM Lucas Cardoso Silva <
cardosolucas61@gmail.com> wrote:
Hi guys,
Here comes the summarized Marvin mission:
The Apache Marvin-AI platform aims to offer a practical and standardized
solution to help its users to perform data exploration, model development
and application lifecycle management, aiming to offer: scalability,
language agnosticism and a
Hi guys!
Great Lucas, I will wait a couple of days to see if anyone has other things
to add, and then we can close this phase!
Wei, we can discuss how to make the data pipelines easier to the users in
another step of the evaluation. With the experience of the users and
developers with this topic
Hello Lucas,
I am thinking of processing JSON or XML files with a hierarchy dynamic
structure.
Or building a pipeline to crop image with object detection metadata.
Data preparation can be very messy,
I wonder if we can have a stage to handle both batch and streaming
processing well.
I simply
Hi folks,
In regards to the mission, you're correct. If I could summarize it, it
would be like: *to help its users to perform data exploration, model
development and application lifecycle management*.
I'm all in for having a better integration with Kubernetes. I think that
the first step is to
I think deploying to K8S does expend our capabilities for inference scaling
and managing.
I am not familiar with Luigi, but it makes sense since we are going to
setup data pipelines.
Best Regards,
Wei
On Wed, Jul 29, 2020 at 5:32 AM Lucas Cardoso Silva <
cardosolucas61@gmail.com> wrote:
>
Great Wei! I find the suggestions really interesting. I think we can work
with the deployment on K8s. The idea of it in Marvin would be, after
development, the user would give some parameters and a script would
facilitate a deployment in a kubernetes cluster, right? Regarding data
acquisition, I
Hello Lucas,
I have some ideas:
1. Should we consider to use K8S or similar tools for inference container
scaling and management?
Marvin's current container management is not as powerful as some container
focus projects.
K8S can also be deployed into most environments now.
2. Is our current
Hi guys.
I would like to know if anyone else has any ideas about this evaluation
phase. Both the opinion of those who have been in the community for a long
time and those who are still getting to know Marvin is now important for
this step, so your suggestion or validation of the initial text is
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