Looking to learn Data Science or Machine Learning for free? Here are 5 excellent books you can access online — covering Python, ML, Deep Learning, Bayesian methods, and Statistics.
1. Python Data Science Handbook
- What it covers: NumPy, Pandas, Matplotlib, and introductory Machine Learning
- Author: Jake VanderPlas
- Link: jakevdp.github.io/PythonDataScienceHandbook A must-read for anyone starting with Python for data analysis.
2. Deep Learning
- What it covers: Full deep learning theory and practice
- Authors: Ian Goodfellow, Yoshua Bengio, Aaron Courville
- Link: deeplearningbook.org This is the definitive deep learning book, used in many university courses.
3. Probabilistic Programming & Bayesian Methods for Hackers
- What it covers: Bayesian thinking with Python and PyMC
- Author: Cameron Davidson-Pilon
- Link: GitHub A fun, practical guide to understanding Bayesian statistics through Python.
4. Dive into Deep Learning
- What it covers: Hands-on deep learning with PyTorch and MXNet
- Authors: Aston Zhang, Zachary C. Lipton, Mu Li, Alex Smola
- Link: d2l.ai Perfect for learners who want practical coding examples alongside theory.
5. Think Stats
- What it covers: Introduction to probability and statistics using Python
- Author: Allen B. Downey
- Link: greenteapress.com/wp/think-stats-2e/ Great for beginners to understand statistical thinking with Python examples.
💡 Tip: Bookmark these books and follow along with the exercises — learning by doing is the fastest way to become proficient.
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