I’m trying to learning machine learning from a more mathematical/theory side of machine learning just so its easier for me to understand AI/ML papers that are coming out just to keep up with them. I would say that I have a basic understanding of AI/ML but more so on the applied side like in Keras, TF, PyTorch somewhat but I feel like I am lacking on my understanding on the mathematical side of AI/ML. So any books and course recs for that?
Mathematics for Machine Learning by Marc Deisenroth and Deep Learning by Ian Goodfellow. Two great books for theory but practice always helps too.
I also recommend Deep Learning by Goodfellow. Long chapter about the mathematical foundations. I found it very insightful as side lecture during my studies. Also, the online version is free.
ESL by Hastie and Tibshirani https://hastie.su.domains/ElemStatLearn/
Pattern Recognition and Machine Learning from Bishop is really good, imho. Its relatively math-heavy, so depending on your skill, reading Mathmatics for ML or Linear algebra and optimization for ML by c. aggarwal might be a good idea.
How is that Aggarwal book? I love Bishop and MML. Thinking about picking it up too.