[mlpack] (no subject)

[Divyam Khandelwal]

Hello Sir Ryan Curtin and Sumedh Ghaisas,
   I read  about archives in mailing list so I firstly  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’m been an active C,C++ coder for many years now. I’m
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 top of bugs should
i solve in this topic
     Thanking You
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