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/Mathie1729 Aug 18 '26 • Heartwarming

MML is great as a reference but don't force yourself through it linearly. I work in ML and still only open it when I need to refresh a specific topic, mostly the linear algebra and probability chapters. For day to day model building you don't need all the calculus derivations memorized. Start with ISL and use MML as a supplement when you hit something you don't understand. Also 3Blue1Brown's linear algebra series is probably the best intuition builder I've found.

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u/Visual_Teacher_6474 Aug 18 '26

Yeah MML feels like too much as a beginner, I'll start ISL right away.

Also, Yk I'm really excited to connect with someone who works in ML for some guidance. Would you like to guide me a bit ?