I've been learning machine learning for the past few weeks from books and online courses. The books I've been reading, and currently still reading is "Hands-On Machine Learning with Scikit-Learn and TensorFlow" and I also read a little bit of "Essential Math for Data Science". However, my main concern is these books tend to try to explain the math, but they don't really put that much detail, so I'm confused with some parts of the implementations of the models like softmax regressions with stochastic-GD.
I would like some suggestions on where I can learn the math and the implementations well. I would love there's a single source for all this because I tend to struggle to connect the strings from multiple different sources into 1. Is there any good math for data science books? It doesn't have to contain a lot of codings.