[kgwgk]

I think Efron & Hastie may be a bit too advanced and terse for the OP. They cover many things in not so many pages and "our intention was to maintain a technical level of discussion appropriate to Masters’-level statisticians or first-year PhD students."

But given that they distribute the PDF for free it's worth checking out. Hastie, Tibshirani & Friedman's The Elements of Statistical Learning and the watered-down and more practical Introduction to Statistical Learning are also nice. All of them can be downloaded from https://web.stanford.edu/~hastie/pub.htm

[achompas]

Elements of Statistical Learning is the other text I came in here to recommend.

One of my most valuable activities in grad school was printing and studying each chapter of EoSL.

It's a comprehensive text on the fundamentals of statistics and machine learning, a solid foundation for the cutting-edge techniques relying on deep learning and reinforcement learning.