My ML reading list

My view of  methods in ML is formed primarly by The Elements of Statistical Learning. A nice introduction (with a recent new edition) is An Introduction to Statistical Learning.

The books that I am trying to find time to go through are:

Similar sites

Bulgarian researchers in probability (with similar sites) that I know of are E. Dimitrov, I. Hartarsky and L. Lichev.

Additionally, you can explore S. Apostolov's blog, which covers a wide range of intriguing mathematical subjects.


My master's thesis was going through Cutoff on all Ramanujan Graphs by E. Lubetzky and Y. Peres for which I clarified the proofs and found a non-trivial mistake (in Proposition 6, p<2). I was extremely lucky to be supervised by J. Salez.

I have written notes for the entry exam for the PhD program in FMI and for the exam after the first year and second year in it.

I often recommend the online course Financial Markets and the specialization Deep Learning. It turns out that Machine Learning in Coursera is the first course in the subject for a lot of people. 


I appreciate the general concept of crowdfunding so here's something kind of similar (which maybe should not be here :D)