Answers inline below.
Trevor Grant Data Scientist https://github.com/rawkintrevo http://stackexchange.com/users/3002022/rawkintrevo http://trevorgrant.org *"Fortunate is he, who is able to know the causes of things." -Virgil* On Tue, Feb 7, 2017 at 2:31 PM, Saikat Kanjilal <sxk1...@hotmail.com> wrote: > @Trevor Grant > > The landscape in machine learning is getting more and more diluted with > lots of tools, here's a question, given that some folks are taking R and > connecting it to spark and map reduce to make the R algorithms work at > scale (https://msdn.microsoft.com/en-us/microsoft-r/scaler/scaler) what > would be the additional value added in porting the R code using the > algorithms/samsara framework, to me the MRS efforts and the approach you > are proposing are 2 parallel tracks, Correct, one is a commercial product by Microsoft- the other is a business-friendly open source Apache Software Foundation Project. > as far as the barriers to entry to contributing I think its largely due to > the complexity of the codebase and the lack of familiarity with Samsara, This is what we hope to overcome with Algorithms framework and perhaps more documentation. I'd love to help create some good docs/tutorials on both the algorithms > framework and samsara when and where it makes sense, Would love the help- will be easier once we get migrated to Jekyll. (More motivation to do this). > however I feel like it'd be useful to really identify the use cases where > using the algorithms/samsara approach has clear wins versus MRS When you don't want to pay Microsoft to use your work in production. > with spark or spark by itself or python/scikit-learn, Out of scope for Mahout project, but I do have a talk forth coming that will address this- stay tuned. > I've found that in general people dont really need custom algorithms in > datascience , they typically are answering some very basic classification > or clustering question and can use linear/logistic regression or a variant > of kmeans. That has not been my experience. In fact quite the opposite- most people need more depth to their algorithms and many other big data ML packages imply they have more depth than basic linear/logisitc regresion + kmeans, but in fact that is all their is. Not to say one is right or wrong- the data scientists who are happy with simple tools can find them in SparkML/FlinkML, those who need more advanced tools may turn to Mahout. > I'd also like to help dig into some use cases with Samsara and put those > use cases maybe in the examples section. > Tutorials would be great- q.e.d. - more documentation would be helpful. > > Thoughts? > > ScaleR Functions - msdn.microsoft.com<https://msdn.microsoft.com/en-us/ > microsoft-r/scaler/scaler> > msdn.microsoft.com > The RevoScaleR package provides a set of over one hundred portable, > scalable, and distributable data analysis functions. This topic presents a > curated list ... > > > > > ________________________________ > From: Trevor Grant <trevor.d.gr...@gmail.com> > Sent: Tuesday, February 7, 2017 8:47 AM > To: user@mahout.apache.org; isa...@apache.org > Subject: Re: Mahout ML vs Spark Mlib vs Mahout-Spark integreation > > The idea that Andy briefly touched on, is that the Algorithm Framework > (hopefully) paves the way for R/CRAN like user contribution. > > Increased contribution was a goal I had certainly hoped for. I have begun > promoting the idea at Meetups. There hasn't been a concerted effort to > push the idea, however it is a tagline / call to action I am planning on > pushing at talks and conferences this spring. Thank you for raising the > issue on the mailing list as well. > > Using the Samsara framework and "Algorithms" framework, it is hoped the the > barrier to entry for new contributors will be very low, and that they can > introduce new algorithms or port them from R. Other 'Big Data' Machine > Learning frameworks suffer because they are not easily extensible. > > The algorithms framework makes it (more) clear where a new algorithm would > go, and in general how it should behave. E.g. This is a Regressor, ok > probably goes in the regressor package- it needs a fit method that takes a > DrmX and a DrmY, and a predict method that takes DrmX and returns > DrmY_hat). The algorithms framework also provides a consistent interface > across algorithms and puts up "guard rails" to ensure common things are > done in an efficient manner (e.g. Serializing just the model, not the > fitter and additional unneeded things, thank you Dmitriy). The Samsara > framework makes it easy to 'read' what the person is doing. This makes it > easier to review PRs, encourages community review, and if (hopefully not, > but in case it does happen) someone makes a so-called 'drive by commit', > that is commits an algorithm and is never heard of again, others can easily > understand and maintain the algorithm in the persons absence. > > There are a number of issues labeled as beginner in JIRA now, especially > with respect to the Algorithms package. > > It would probably be good to include a lot of this information in a web > page either here https://mahout.apache.org/developers/how-to-contribute. > html > Apache Mahout: Scalable machine learning and data mining< > https://mahout.apache.org/developers/how-to-contribute.html> > mahout.apache.org > How to contribute¶ Contributing to an Apache project is about more than > just writing code -- it's about doing what you can to make the project > better. > > > > or on a page that is linked to by that. > > Which leads me in to the last 'piece of the puzzle' I would like to have in > place before aggressively advertising this as a "new-contributor friendly" > project, migrating CMS to Jekyll > https://issues.apache.org/jira/browse/MAHOUT-1933 > > The rationale for that is so when new algorithms are submitted, the PR will > include relevant documentation (as a convention) and that documentation can > be corrected / expanded as needed in a more non-committer friendly manner. > > > > > > > Trevor Grant > Data Scientist > https://github.com/rawkintrevo > [https://avatars3.githubusercontent.com/u/5852441?v=3&s=400]<https:// > github.com/rawkintrevo> > > rawkintrevo (Trevor Grant) · GitHub<https://github.com/rawkintrevo> > github.com > rawkintrevo has 22 repositories available. Follow their code on GitHub. > > > > http://stackexchange.com/users/3002022/rawkintrevo > User rawkintrevo - Stack Exchange<http://stackexchange. > com/users/3002022/rawkintrevo> > stackexchange.com > Fortuna Audaces Iuvat ~Chance Favors the Bold. top accounts reputation > activity favorites subscriptions. Top Questions > > > > http://trevorgrant.org > [https://s0.wp.com/i/blank.jpg]<http://trevorgrant.org/> > > The musings of rawkintrevo<http://trevorgrant.org/> > trevorgrant.org > Hot-rodder, opera enthusiast, mad data scientist; a man for all seasons. > > > > > *"Fortunate is he, who is able to know the causes of things." -Virgil* > > > On Tue, Feb 7, 2017 at 4:30 AM, Isabel Drost <isa...@apache.org> wrote: > > > On Wed, Feb 01, 2017 at 03:32:24PM -0800, Dmitriy Lyubimov wrote: > > > Isabel, if i understand it correctly, you are asking whether it makes > > sense > > > add end2end scenarios based on Samsara to current codebase? > > > > Sorry for being fuzzy. The meta question that I'm trying to find an > answer > > for > > is if there's something can/ should be done to increase the number of > > people > > that potentially could be assimilated and turned into committers one day. > > One > > specific idea I had on my mind was to make the project easier to use for > > beginners, one idea to get that accomplished I had was to focus on end to > > end > > implementations of popular use cases. (Sorry, fairly meta...) > > > > > > > The answer is, absolutely. Yes it does for both rather isolated issues > > > (like computing clusters) and end-2-end scenarios. > > > > > > The only problem with end 2 end scenarious is they often difficult to > > > demonstrate with batch-oriented coputational system only. That's what > > > prediction.io kind of picked on with COO, they included all of data > > > ingestion, computation and real time scoring queries. > > > > > > But yes, there's, absolutely, tons of value in that. Not everything > fits > > > quite nicely, and not everything fits end-2-end (just like with R), but > > > some fairly significant pieces do fit to be written on top. > > > > Makes sense. > > > > > > > > Where do we start? ;) > > > > > > > > > > I would start with figuring a problem I want to solve AND I have a > budget > > > to do it AND i can legally contribute on behalf of the IP owner. > > > > I guess given the meta explanation above - if increase in contributions > > was a > > goal one could also think about making potential areas of contribution > > explicit > > and highlight the value the project brings compared to other systems > with a > > specific focus on samsara. That's another angle of me asking weird > > questions > > here. > > > > > > > Then we can think of whether it is a good fit (Samsara is mostly > limited > > to > > > tensor based data only, just like Mapreduce DRM was/is). Some things > may > > > not have a convenient algebraic formulation. > > > > +1 > > > > Isabel > > > > -- > > Sorry for any typos: Mail was typed in vim, written in mutt, via ssh > (most > > likely involving some kind of mobile connection only.) > > >
