AIBooks.
Kickstart your journey in data science and machine learning with our free, complete books. You'll find everything from first principles to advanced topics, with runnable notebooks in every chapter.
So You Want to Be a Data Scientist
Python Primer for Data Science
A complete path from your first import to code other people depend on. Twenty-five short chapters covering the Python language itself, NumPy and pandas, loading and cleaning real data, visualisation, the statistics you need to make an honest claim, and the scikit-learn interface. Written for someone who has never done data science, and assumes no mathematics beyond secondary school.
Learn ML Algorithms
From first principles to the one line you would ship
Every algorithm four ways: the intuition, the mathematics, an implementation from scratch, and the one line of scikit-learn you would actually ship.
How to Fine-Tune an LLM
Data, LoRA, evaluation, and what it costs to serve
When fine-tuning is the wrong answer, and how to do it properly when it is the right one. Data, LoRA, training, honest evaluation, and what it costs to serve.
How the notebooks work
Chapter code lives as Jupyter notebooks in a public GitHub repository. ClickOpen in Colab on any chapter and it loads into a free Google Colab runtime in your browser. Nothing to install, nothing to configure, and your edits are yours. Fork the repository if you want to keep them.