Books

A complete foundation for Statistics, also serving as a foundation for Data Science. Leanpub revenue supports OpenIntro (US-based nonprofit) so we can provide free desk copies to teachers interested in using OpenIntro Statistics in the classroom and expand the project to support free textbooks in other subjects. More resources: openintro.org.

Master language models through mathematics, illustrations, and code―and build your own from scratch!

The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. This book introduces concepts from probability, statistical inference, linear regression and machine learning and R programming skills. Throughout the book we demonstrate how these can help you tackle real-world data analysis challenges.

The book is also available in paperback for $25. Paperback royalties go to OpenIntro (US-based nonprofit), and the optional Leanpub PDF contributions go to authors to fund their time on this book.

Everything you really need to know in Machine Learning in a hundred pages.

This book brings the fundamentals of R programming to you, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization. The skills taught in this book will lay the foundation for you to begin your journey learning data science. Printed copies of this book are available through Lulu.

It's never been easier to build an AI agent — and never been harder to make one that actually works. This book takes you from language model foundations to production-ready multi-agent systems with the depth to predict failure before it happens, engineer graceful degradation over catastrophic failure, and take absolute architectural ownership. Get the paperback from amazon.

Introduction to Statistics for the Life and Biomedical Sciences is the 4th official OpenIntro book and has been written to be used in conjunction with a set of self-paced learning labs. These labs guide students through learning how to apply statistical ideas and concepts discussed in the text with the R computing language.

"Data Science Project: An Inductive Learning Approach" provides a comprehensive methodology for data science project development, emphasizing software engineering principles essential for reliable solutions. Dr. Filipe Verri, a senior data science project manager, guides readers through the origins, scope, and key concepts of data science. This book covers machine learning, data handling, and rigorous validation techniques, all essential for preparing readers to tackle complex, real-world projects.

This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science. Printed copies are available through Lulu.

Launch Price $9.99 Special! — price will increase as I plan to steadily add more chapters over the coming weeks.

Completely hands-on so that you can start the real work!

Build GPT-2, Llama 3, and DeepSeek from scratch in PyTorch. Every chapter has runnable end-to-end code and loads real pretrained weights. Goes well past where most LLM tutorials stop.

Bridge AI and science with this hands-on guide. Whether you're a researcher learning ML or an engineer entering scientific applications, build real systems across chemistry, biology, physics & climate. Master Transformers, Diffusion Models & GNNs for scientific discovery. 500+ pages, 50+ Colab notebooks. Design molecules, predict proteins, accelerate climate models—all hands-on, zero setup required.

Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst. Instead of showing theory first and then applying it to toy examples, we start with actual applications and describe the theory as it becomes necessary to solve specific challenges. The book includes links to computer code that readers can use to follow along as they program.