The quest for knowledge never ends. As 2025 approaches, machine learning enthusiasts are hunting for resources that won’t break the bank. Good news—there are tons of free books out there. No excuses for not leveling up your skills now.

For those needing solid theoretical foundations, “Foundations of Machine Learning” by Mohri and colleagues breaks down PAC learning, SVMs, and boosting principles. Free.

Or grab “Understanding Machine Learning” by Shalev-Shwartz and Ben-David—mathematical derivations included. Also free. The statistical crowd gravitates toward Hastie’s “Elements of Statistical Learning.” It’s thorough. And yes, free online.

Mathematical rigor without financial pain—these classics demystify the theory that powers modern algorithms.

Python coders have it made. “An Introduction to Statistical Learning With Applications in Python” offers code you can actually use. R programmers aren’t left out either—there’s an R version too. Both cost exactly zero dollars.

Davidson-Pilon’s “Probabilistic Programming & Bayesian Methods for Hackers” delivers IPython notebooks ready for tinkering.

Deep learning? Goodfellow’s aptly named “Deep Learning” is the bible of neural networks. It’s online. Free. The book’s HTML format allows for easier access and reading online, though printing works best through Chrome browser.

Nielsen’s “Neural Networks and Deep Learning” takes a more biological approach. Also free. “Dive into Deep Learning” even supports multiple frameworks—PyTorch, TensorFlow, whatever you’re into.

Math-lovers rejoice. “Mathematics for Machine Learning” by Deisenroth covers all the linear algebra and calculus you’ll need.

MacKay’s “Information Theory, Inference, and Learning Algorithms” digs into theoretical underpinnings. Both won’t cost you a dime.

Let’s be real. Some of these books are dense as hell. Not bedtime reading material. But they’re free, so who’s complaining?

The landscape of machine learning evolves daily. Keeping up seems impossible sometimes. But with these resources, you’re out of excuses. They’re accessible. They’re thorough. They’re free. What more could you want? Well, maybe more time to actually read them all.

Bookmark this collection for future reference as the page will be regularly updated with new AI books as they become available.