
Dive into Python's advanced possibilities, including algorithm analysis, graphs, scale-free networks, and cellular automata with this in-depth, hands-on guide.
Here's a few:
Think Complexity
https://github.com/AllenDowney/ThinkComplexity2
Think DSP
https://github.com/AllenDowney/ThinkDSP
Think Stats
https://github.com/AllenDowney/ThinkStats/
Think Bayes
- Think Python
- Think Data Structures
- Think Java
- Think Perl6 (!)
- Modeling and Simulation in Python
- Probably Overthinking It
And more [1]. He's a prolific writer, and very generous for offering many of them for free. I read several of them online or through O'Reilly, and bought printed copies just to appreciate his work. Really enjoyed Think DSP, Think Complexity, Think Bayes, etc.
[1] https://www.amazon.com/stores/Allen-Downey/author/B001O8NBPS
> Moreover, the American Institute of Mathematics maintains a list of approved open-source textbooks. https://aimath.org/textbooks/approved-textbooks/
I also like the (free) Green Tea Press books: Think Stats, Think Bayes, Think DSP, Think Complexity, Modeling and Simulation in Python, Think Python 2e: How To Think Like a Computer Scientist https://greenteapress.com/wp/
And IDK how many times I've recommended the book for the OCW "Mathematics for Computer Science" course: https://ocw.mit.edu/courses/electrical-engineering-and-compu...
There may be a newer edition than the 2017 version of the book: https://courses.csail.mit.edu/6.042/spring17/mcs.pdf
