I have found coursed that has prerequisite of math for learning machine learning and also they provide an introduction to these but are unable to cover it entirely.
The in-depth mathematical foundation required for machine learning cannot be learned from a single book, because machine learning utilizes concepts from different fields of mathematics e.g.
- Linear Algebra (https://www.amazon.com/Introduction-Linear-Algebra-Gilbert-Strang/dp/0980232775)
- Probability Theory and Statistics (https://www.amazon.com/Probability-Statistics-Engineers-Scientists-Anthony/dp/1111827044)
- Multivariate Calculus (https://www.wiley.com/en-us/Calculus%2C+10th+Edition-p-9780470647721)
Mathematics of Machine learning by MITopencourseware; This course I would definitely recommend as it increased my in-depth understanding of ML via Maths.
Link: https://ocw.mit.edu/courses/mathematics/18-657-mathematics-of-machine-learning-fall-2015/
http://users.math.cas.cz/~hvle/ML2018a.pdf
or you can have a look in the following discussion.
https://www.quora.com/What-are-the-best-math-books-for-machine-learning
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