Free monthly learning resources and insights https://gilesknowledge.substack.com/
Here are the links to the machine learning resources mentioned:
http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
https://opentechschool.github.io/python-data-intro/core/recap.html
https://www.kaggle.com/learn/intro-to-machine-learning
https://developers.google.com/machine-learning/crash-course/
https://www.tensorflow.org/tutorials
https://machinelearningmastery.com/start-here/

https://mml-book.github.io/
https://www.probabilitycourse.com/chapter1/1_1_0_what_is_probability.php
https://www.statisticsdonewrong.com/
https://github.com/ageron/handson-ml3
https://courses.cs.duke.edu/spring20/compsci527/papers/Domingos.pdf
https://datascience.stackexchange.com/
https://stats.stackexchange.com/?tags=machine-learning
https://pytorch.org/tutorials/
https://scikit-learn.org/stable/tutorial/index.html

That’s 16 in total!

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πŸ“— Python Crash Course 2nd Edition https://amzn.to/33tATAE
πŸ“˜ Automate the Boring Stuff with Python https://amzn.to/3qM1DFl
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πŸ“• Python Programming An Introduction to Computer Science https://amzn.to/33VeQCr
πŸ“— Invent Your Own Computer Games with Python https://amzn.to/3FM3H4b

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https://python-programming.quantecon.org/intro.html
(This is a great introduction to python)

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