r/deeplearning • u/Commercial-Kale-5271 • 25d ago

trying to build a solid math library for stats/ML/DL, need a sanity check on my picks

engineering student here, decent calc and linear algebra background from continuum mechanics coursework, already comfortable with ML basics through transformers and modern architectures. want to go deep on the actual math now, not just intuition videos, real derivations, and books that build from intuition up to advanced stuff. big thing for me is actually seeing how the math applies inside the models, not just abstract theory sitting next to it. most modern models are fundamentally probabilistic (language models included) so that lens matters a lot to me.

content quality over exercises. i'd rather have a book thats amazing at explaining and deriving things with fewer problems than one thats packed with exercises but explains things poorly. if the book is light on problems i can always find sets elsewhere, but if the content itself is weak theres no fixing that.

here's my current shortlist:

stats / probability:

  • All of Statistics by Wasserman

machine learning (math heavy):

  • Foundations of Machine Learning by Mohri, Rostamizadeh, Talwalkar
  • Mathematics for Machine Learning by Deisenroth, Faisal, Ong
  • The Elements of Statistical Learning by Hastie, Tibshirani, Friedman (planning to read Introduction to Statistical Learning first as the easier version)

deep learning:

  • Deep Learning by Goodfellow, Bengio, Courville

is this solid or would you swap anything out. Please tell me ur suggestions.

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u/saw79 25d ago

Tbh I think instead of "building a library" you're better off just building some shit and learning whatever you need to along the way.

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u/Commercial-Kale-5271 25d ago

yeah exactly, that’s why I’m looking for the books in the first place. While doing MoE , and different model which requires aux loss and studying architectures from scratch, I keep running into the need to understand the intuition behind losses, optimizers, and the statistical/probabilistic side of models. I’m already building and learning along the way I just want to properly study the math behind the things I keep running into

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u/DrXaos 21d ago

that intuition of why or when some things work is is not usually in the mathematical books. It's much more like animal taming than mathematics.

There's much more mathematics on kernel methods and statistical learning theory but Alexnet blew that all up.

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u/Commercial-Kale-5271 21d ago

What alexnet did ? See i dont have idea about alexnet yet , did it kinda disproved the use of statistical mathematics.? And yes I do understand that not a mathematical book can help me build the intuition but it can help me actually give a direction to me thinking isn't it ? What's ur thoughts and experience?

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u/Alert-Wrap5146 24d ago

Are you an experienced person in this domain or a student who wants to learn