[mlpack] Cross-validation and hyper-parameter tuning infrastructure

[Kirill Mishchenko]

Hi,

my name is Kirill. I’m interested in the contribution to the project “Cross-validation and hyper-parameter tuning infrastructure”. I have already gone through some starting steps, like building the code and running a few ML algorithms (more precisely, I have did it for Linear Regression and Logistic Regression). Now I’m going to read rigorously the wiki page "Design Guidelines” and to go through the interfaces in the code base . Are there any other suggestions how I can start to work on the project? Is there some way to make a related small contribution to the code base? 

Briefly about myself. I am a PhD student working on Computational Humor. More precisely I’m working on the problem of finding/generating a humorous response given a textual input. My programming experience includes two summer internships in big Russian IT companies: in one I was programming in C# (SKB Kontur), in another I was a C++ developer (Yandex search). In daily life I use Python. I have taken the online course Machine Learning by Stanford (Coursera), as well as some other courses related to ML (AI by Berkeley (EdX), Deep Learning by Google (Udacity), and others).

Best regards,

Kirill Mishchenko



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