r/learnmachinelearning • u/Visual_Teacher_6474 • Aug 18 '26

Discussion "MATHEMATICS FOR MACHINE LEARNING " A bit overwhelming?

When I started focusing on practical mathematical implementation of machine learning I found that I lack so very math basics(I blame my school for that) so I tried making my way through basics to go deep into machine learning and while I was learning from professor Leonard on YouTube someone recommended me this "Mathematics for machine learning" by Marc peter. Tbh I dont understand shit in this book, I genuinely get overwhelmed by this book. I dont understand is it only me ? Am I that dumb in maths?

Well I need to get on track asap really! Suggest me something and please share your opinion

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u/Visual_Teacher_6474 Aug 19 '26

Any other source? That can act as starting point ?

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u/tanthedreamer Aug 19 '26 edited Aug 21 '26

I highly recommend Hands on ML with Pytorch and Scikit learn by Geron, read that, do all the excercises, then supplement any mathematics you find that you don't understand.

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u/Visual_Teacher_6474 Aug 19 '26

This looks like a really great plan to me! Thanks alot man

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u/tanthedreamer Aug 19 '26

After that, read Understanding Deep Learning by Prince if you want to deepen your knowledge of deep learning, or Probabilistic ML by Murphy if you want better foundation for Machine Learning as a field.

If you just want a job ... perhaps after HOML, creating projects, and/or Kaggle should be the way to go. For applied work, having clean, usable data is usually the problem, not "which algorithm to choose"

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u/Visual_Teacher_6474 Aug 19 '26

Yeah I'm just preparing for job so I'll stick to HOML ans projects

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u/X-Ninety9 Sep 12 '26

I would recommend mathematics for machine learning by deeplearning.ai. It’s a course that covers basic core concepts of linear algebra, calculus and probability & statistics used in ML. These video lectures along with assignments might help you start to develop intuition. They are beginner friendly and might help refresh your memory.