I have always emphasized on the importance of mathematics in machine learning.

Here is a compilation of resources (books, videos & papers) to get you going.

(Note: It& #39;s not an exhaustive list but I have carefully curated it based on my experience and observations)
https://abs.twimg.com/emoji/v2/... draggable="false" alt="๐Ÿ“˜" title="Blaues Buch" aria-label="Emoji: Blaues Buch"> Probability Theory: The Logic of Science

by E. T. Jaynes

Note: In machine learning, we are interested in building probabilistic models and thus you will come across concepts from probability theory like conditional probability and different probability distributions.
https://abs.twimg.com/emoji/v2/... draggable="false" alt="๐Ÿ“œ" title="Schriftrolle" aria-label="Emoji: Schriftrolle"> The Matrix Calculus You Need For Deep Learning

by Terence Parr & Jeremy Howard

https://arxiv.org/abs/1802.01528 

Note:">https://arxiv.org/abs/1802.... In deep learning, you need to understand a bunch of fundamental matrix operations. If you want to dive deep into the math of matrix calculus this is your guide.
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