Hi, I dont know if this is the right place to ask this question, but what book should I study for learning the theoretical math part on machine learning? I’ve implemented ml as in programming so I have a good grasp of the “big picture”, but I want to start reading research papers and understand the math part. I already have a solid understanding of calculus, linear algebra, statistics and probability. As of now I am seeing

1. Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) by Kevin P. Murphy
2. Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz and Shai Ben-David

but I’m not sure which one to get. Any recommendation on which one & why would be a great help for me!

I’ve also had some recommendations on “ Elements of Statistical Learning” by Trevor Hastie and took a look into that, but I want something a bit more advanced than that.