This is what I did when I started getting into maths for machine learning.
1) Mathematics for Machine Learning: Linear Algebra coupled with 3b1b: Essence of linear algebra
Then
2) 3b1b: Essence of Calculus, Mathematics for Machine Learning: Multivariate Calculus and Khan Academy: Multivariate Calculus by 3b1b
After that, I did Andrew ng's machine learning and with all the understanding of mathematics in my head, this course turned out to be very easy.
Then after,
3) I learned Numpy, Pandas and did Mathematics for Machine Learning: PCA
I'm doing deep learning specialization and all these maths are helping me understand faster.
I suggest you, do the maths first and then the algorithms. You'll thank yourself later!
Good luck!