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[D] Please suggest me material fo maths

I want to deeply understand maths related to deep learning and machine learning. I am mentioning my background so someone can suggest me some materials for learning purpose.

Backgroud: Undergrad completed.I have completed deep learning specialization. I can calculate derivation of different things like sigmoid and thanks to deep learning specialization, i also know how actually neural network work. I have also implemented few research paper on my own and open sourced the code.

But, now i want to re-learn calculus, linear algebra and probabilities for better understanding of dl and ml methods. Why we choose sigmoid or tanh, how actually relu is implemented and how actually auto-grad works. things like that.

I searched for some book on calculus and linear algebra but recommendations are to off. Many people recommended Spivak and i started reading it. but starting chapter looks too much dull and only explains theoretically. I want materials where i can understand thing pratically. If possible, then with programming exercises.

please suggest for calculus, LA and Stats.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.