A selection of data science books in python?

Question

Python

Hello!
For quite a long time I have been engaged in data-science - models, parameter estimation, hypothesis testing, etc.
However, I feel some unsystematic knowledge on this issue, a typical example - I know how mixtures of Gaussians work and how they can be used in clustering, I can use them with sklearn, but I don’t know how the EM algorithm works. I have a lot of such examples, and I feel like a code-monkey - I kind of build models, but I clearly lack a deep understanding of the mathematics and methods used in these models.
In this regard, I want to read some weighty, fundamental book about the algorithms, methods and models used in data-science (in Russian or English - it doesn't matter). Tell me where to start?

Answer 1

Scikit has good documentation, including mathematical calculations of algorithms, for example, here about clustering: scikit-learn.org/stable/modules/clustering.html
There are also links to a more detailed description of algorithms.
If you want to level up in algorithms, then I highly recommend the online course https://www.coursera.org/course/ml

Answer 2

Good stuff:
https://sites.google.com/site/fyuugisdfsw/pdf-pyth... - the foundation of the basics.
https://proglib.io/p/7-python-books/ - a selection.
https://bookflow.ru/tag/python/ - selection.
https://www.amazon.co.uk/Python-Users-Data-Science... - also an interesting thing if you are migrating from R.
https://proglib.io/p/python-vs-r/ - Well, actually, what is driving now: R or Py.