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🧠 Top Free AI Books (Legally Available)

1. "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

• 📘 Covers: Neural networks, backpropagation, optimization, deep generative models.

• 🔗 https://www.deeplearningbook.org/

2. "The Hundred-Page Machine Learning Book" by Andriy Burkov

• 📘 Free version available as a PDF by author’s permission.

• 🔗 https://github.com/llSourcell/The_ML_Book

3. "Artificial Intelligence: Foundations of Computational Agents" by David L. Poole and Alan Mackworth

• 📘 A comprehensive academic book covering search, reasoning, learning, and planning.

• 🔗 https://artint.info/

4. "Practical Deep Learning for Coders" (fast.ai) by Jeremy Howard and Sylvain Gugger

• 📘 Focused on hands-on deep learning with PyTorch.

• 🔗 https://book.fast.ai/

5. "Probabilistic Programming and Bayesian Methods for Hackers" by Cameron Davidson-Pilon

• 📘 Bayesian inference explained with Python code.

• 🔗 https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

6. "Machine Learning Yearning" by Andrew Ng

• 📘 A strategic guide to improving ML projects, especially for managers and engineers.

• 🔗 https://www.deeplearning.ai/machine-learning-yearning/

7. "Dive into Deep Learning" by Aston Zhang, Zachary Lipton, Mu Li, and Alexander Smola

• 📘 Interactive Jupyter Notebook-based book using MXNet/Gluon and PyTorch.

• 🔗 https://d2l.ai/