Introduction to computer science for ML I have learned python syntax (from books like fluent python or python cookbook etc.) and I want to learn the underlying concepts of computer science (in an abtract way), do you have some books/courses to suggest to me (others than algorithms and data structures' resources)

I've found a book called Python Programming. An introduction to computer science by John Zelle, but I am worried about the potential huge overlap between the above-mentionned books and this one.

Some books found while brwosing the web, but I don't have an idea about its usefulness : 


Structure and Interpretation of Computer Programs  by Harold Abelson, Gerald Jay Sussman, and Julie Sussman
Compilers: Principles, Techniques, and Tools by Alfred V. Aho
How to design computer programs by  by Matthew Flatt, Matthias Felleisen, Robert Bruce Findler, and Shriram Krishnamurthi
Theory of Computation by Michael Sipser


PS: My backgraound is a Bachelor degree in Mathematics. My goal is to gain sufficient knowledge of CS concepts.

Thanks
Computer science is a very broad field - see this Wikipedia outline. Machine learning is just one topic within the field, and there are other parts of computer science that have little or no overlap with machine learning. For example, the theory of compiler design is unlikely to be of much use to you when studying machine learning.

My suggestion is to approach this from the opposite direction. Start with a text that provides an introduction to machine learning. An introductory text should include an overview of other computer science topics that are pre-requisites. If you want to or need to dig into any these wider topics in more detail, then you have a more focussed goal than trying to understand the whole of computer science.