Thanks a lot Marcus , I pulled an all nighter and went through the list of projects again ( lot of readings ) and i think more than Deep Learning implementations i can make a good contribution by adding the Cross Validation Modules for training algorithms as i felt it suits my existing skill set more than others.I drafted a rough plan of action and also mailed the mentor : Ryan regarding the same.
So this is what i did as of now , 1.Built the code and ran Linear and Logistic Regression. 2.Went through the Linear Regression Module and read the design guidelines page throughly. As its a new one , no relevant issues exist as of now so I would like to start by adding a Cross-Validation module to Linear Regression (will start working on it now) , and once i get accustomed to ML-Packs coding style and API designs i can add further modules for other training algorithms and also optimize my approaches (through better pre-computation etc ). I would love to have your valuable feedback on the plan , would you suggest i do something else that can result in a more productive outcome?. Guidance , suggestions are welcome . Thanking You. Narayan. Indian Institute of Technology , Madras. On Sat, Mar 4, 2017 at 6:13 PM, Marcus Edel <[email protected]> wrote: > Hello Narayan, > > I went through the Project Ideas and the following projects intrigued me > "Essential Deep Learning Modules" and "Reinforcement Learning". I am > reading up > on the models in those topics so that i make an informed decision. > > > Great that you liked the ideas, let us know once you decided which project > you > like to work on so that we can probably brainstorm some ideas. > > Also, The Reinforcement learning and Essential deep learning modules > project has > been discussed at on the mailing list before: > > http://mlpack.org/pipermail/mlpack/2017-March/003095.html > http://mlpack.org/pipermail/mlpack/2017-March/003098.html > http://mlpack.org/pipermail/mlpack/2017-February/003087.html > > http://mlpack.org/pipermail/mlpack/2017-March/003107.html > http://mlpack.org/pipermail/mlpack/2017-February/003092.html > > Note that there are many more posts on this in the mailing list archive > to search for; those are only some places to get started. > > Kindly guide me in getting started with understanding the codebase.I have > it > cloned it , compiled it from source in my local machine and also > implemented few > simple programs from the "getting involved" page. > > > There are some easy issues on GitHub that you might find interesting, we > will > see if we can add more in the next days. Besides that, any contributions > of new > techniques or efficiency improvements for existing implementations are > always > welcome. > > I hope this is helpful, let us know if you have any more questions. > > Thanks, > Marcus > > On 3 Mar 2017, at 19:34, S.NARAYAN ee15b108 <[email protected]> > wrote: > > Hello, > > I am Narayan , an undergraduate student at IIT-Madras.I am interested in > participating in GSoC 2017 with mlpack.I am not new to Machine Learning and > i have worked on a Project in BioInformatics at University of > Angers,France during my summer. > > I am new to ML-Pack and i am really interested in being a long-term > contributor and working on it during summer with or without GSOC stipend.I > went through the Project Ideas and the following projects intrigued me > *"Essential > Deep Learning Modules" and "Reinforcement Learning".* > I am reading up on the models in those topics so that i make an informed > decision. > > Kindly guide me in getting started with understanding the codebase.I have > it cloned it , compiled it from source in my local machine and also > implemented few simple programs from the "getting involved" page. > > and Congrats to ML-Pack for getting accepted to GSOC again.Hoping to have > an eventful summer. > > Thanking You. > Narayan. > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack > > >
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