<div dir="ltr"><div>Hello,</div><div><br></div><div> </div><div>I am Sushmita Singh, studying in pre-final year of Mathematics and Computing at Indian Institute of Technology (BHU)-Varanasi, India. Mlpack is a organization of my interest and I am really looking forward to contributing to Mlpack through or beyond GSoC'16. I feel that Mlpack will provide the advantage to c++ user for using machine learning so they don't have diverted to some other language. </div><div><b><br></b></div><div><b>Relevant Experience:</b></div><div>I have a four-year practice of coding in c, c++, java. I have done projects of ECC (Elliptic Curve Cryptography) at DRDO(Defence Research and development Organization) Delhi which is coded in c++ that has given me experience. I am working on my thesis which is on machine learning so I m process of learning about new algorithm.</div><div><br></div><div><br></div><div>I have built the library in my system and gone through some of the methods provided by mlpack. I m biased towards :</div><div><b>1.conditional decision trees</b> </div><div><b>2.Bayesian</b> <b>algorithms</b>. </div><div>I want to work on <b>Gaussian naive bayers, multinomial naive bayers and conditional decision trees</b>.</div><div> Besides going through methods of density elimination trees, naive bayers, Gaussian Mixture and hidden Markov model, what else should I go through? please guide me further.</div><div><br></div></div>