
But I want to learn ML so digging in. I feel like it is not as bad as I thought it would be, I think the problem with math information is assumes a lot of things. There are tons of notation that is really dense.
My recommendation would be to pick a project or an area, because math is huge. Try to find resources for that. So for ML it is linear algebra and Calculus. Try to find a bunch of resources and get different ways of explaining it.
I highly recommend:
Math for Programmers by Paul Orland
Algorithms and Data Structures in Action (MEAP)
Algorithms of the Intelligent Web 2e
Data Science with Python and Dask
Data Wrangling with Javascript
Get Programming with Haskell
Grokking Algorithms
Grokking Bitcoin
Grokking Machine Learning (MEAP)
Machine Learning in Action
Math and Architectures of Deep Learning (MEAP)
Math for Programmers
Modern Fortran
Practical Data Science with R 2e
Practical Recommender Systems
Quantum Computing in Action (MEAP)
Succeeding with AI
Manning Early Access Program (MEAP) lets folks pre-order works in progress to give early feedback.