[mlpack] GSOC 2016 Contribute to MLPACK

[Divyam Khandelwal]

Hello Sir Ryan Curtin and Sumedh Ghaisas,
   I read  about archives in mailing list so I firstly decided to
build mlpack library and I had compile mlpack tutorial programs and
now I am comfortable with it.Thanks for helping in completing my first
step. I am Third Year B.Tech student CS Undergraduate from Vishwakarma
Institute of Technology,Pune.I am an active C,C++ coder for many years
now. I am currently studying Recommender Systems and I want to explore
it lot by learning new optimization methods and by implementing
it.However, while it is possible for me to improve my knowledge of
recommender system  on the side while studying machine learning (most
of my recommender system was self-taught anyway).I’ve always had a
passion for both programming and mathematics.
   So I want to move towards the second step to solve bug please
direct me how to proceed toward it

   I'm interesrted in Alternatives to neighborhood-based collaborative filtering
   I read about the paper attached on the site. Even I read the matrix
factorization method of Amazon and Netflix which they used and
understood it.
   The reference material I read uptill now is
   =>The given paper
   =>Slideshare giving a brief idea about matrix factorization
   https://www.google.co.in/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&cad=rja&uact=8&ved=0ahUKEwjspY2ngK_LAhXOTI4KHU5NC8kQFgg8MAQ&url=http%3A%2F%2Fwww.slideshare.net%2Fstudentalei%2Fmatrix-factorization-techniques-for-recommender-systems&usg=AFQjCNEtwt1uY6UqtIRV595sg9KSkCX2vg&sig2=OWdhVM1sjWXiSRw10VaCGA&bvm=bv.116274245,d.c2E
   =>Matrix Factorization Techniques for Recommender Systems
 By Yehuda Koren, Yahoo Research
       Robert Bell and Chris Volinsky, AT&T Labs—Research

Please recommend what literature should i read and what type of bugs
should i solve in this topic
     Thanking You