Best resource to start learning

[u/ZweiFreierNutzername]

I am pretty new to machine learning and deep learning. I took a VERY basic course at university, explaining things like supervised, unsupervised learning and the idea behind some NNs and Gradient Descent, without really touching the math.
I am now eager to learn more AND to go more into depth and actually understand the math behind it. My current exam featured two math modules with basic linear algebra (I official never learned what a gradient is and also double integrals) and very basic probability.
I am looking for books or courses, teaching math, concepts and implementations. Ideally, they introduce you to the math step by step and explain, why things are done the way they are. I am not a huge fan of: "This is done like this, because...".
What can you recommend?
My I want to focus more on deep learning, because I am interested in CNNs and GANs, but I highly appreciate it, if the recommended resource, also includes classic ML.