[ryankupyn]

I'm a big fan of ISL - one of the best intro machine-learning oriented textbooks out there IMO. If you're looking for book that still offers a broad survey while going a bit deeper into the math, I recommend Elements of Statistical Learning as well (they share 2 authors):

https://web.stanford.edu/~hastie/Papers/ESLII.pdf

[_fullpint]

ESL is really really good. Absolutely cannot be recommended enough. I’ve worked through at few times and it’s a great book to have on the shelf.

ISl is good but as it being an introduction book — the lack of higher order math wasn’t my favorite.

[abhgh]

Recommendation for ESL seconded. One of the best ML books in terms of writing, development of intuition, breadth of topics (ofc doesn't cover everything, esp deep learning).

What I love about the book is how the topics are "connected" so to speak. The narrative within a theme is typically "let's look at problem P, here's technique Q to solve P, but if you thought about P slightly differently you would see something like technique R would also work, so let's talk about that now".

The level of math might be tough for a beginner though.

[madiyar]

I can also recommend https://github.com/maitbayev/the-elements-of-statistical-lea... as a supplementary resource that reproduces graphics and implements algorithms from scratch from the book.