Books

Not just for mathematicians and detectives! Learn the basics of logic and its many applications, including advanced testing, constraint solving, function composition, and code proofs. Over 50 exercises and 20 sample programs are included. No prior math background required!

If you are able to contribute, it will go to support OpenIntro (not the author), a US-based nonprofit working to spread open materials, e.g. by providing desk copies to instructors considering this text. This listing is in collaboration with the textbook's author, Jim Hefferon. Linear Algebra's official websitePaperbacks are $22openintro.org

This book supplements the DM for CS Specialization at Coursera and contains many interactive puzzles, autograded quizzes, and code snippets. They are intended to help you to discover important ideas in discrete mathematics on your own. By purchasing the book, you will get all updates of the book free of charge when they are released.

The book contains the full transcript of Software Diagnostics Services training with 16 hands-on exercises on various topics related to Linux API.

Leanpub revenue supports OpenIntro. OpenIntro is a US-based nonprofit that provides textbook services to help increase adoption of OER textbooks and save students money. These textbook services are fully financed by Leanpub contributions on supported books. APEX Calculus website: apexcalculus.comOpenIntro website: openintro.org

The essentials of making predictions using supervised regression and classification for tabular data. Tech stack: python, pandas, scikit-learn, CatBoost, LightGBM, XGBoost, TabPFN, TabICL

Pedagogical Philosophy of the BookThis book is designed with three guiding principles:1.     Clarity over Formalism While maintaining mathematical accuracy, the book avoids unnecessary formalism that can confuse beginners. Instead, it uses intuitive explanations, diagrams, and real-world analogies.2.     Integration of Computation Every mathematical concept is tied to computational practice. Readers are encouraged to implement simple code snippets (in Python, NumPy, or similar tools) to reinforce their understanding.3.     Balance Between Breadth and Depth The book covers the essential calculus concepts in sufficient depth to support AI applications, without delving into overly abstract branches that have limited relevance to machine learning. Who Should Read This Book?·        Students of Computer Science, Data Science, and AI – who want to strengthen their mathematical foundation for advanced courses and projects.·        Researchers in AI – who need a refresher or structured guide to connect calculus with modern algorithms.·        Industry Professionals and Engineers – who want to move beyond using libraries like TensorFlow or PyTorch blindly and instead gain an understanding of the mathematics behind the models.·        Educators – who seek a resource that connects abstract mathematics with practical AI examples for teaching purposes.Benefits of Studying This Book1.     Builds Mathematical Confidence – Readers who once found calculus intimidating will discover a fresh, accessible perspective tailored for AI.2.     Enables Deeper Understanding of Algorithms – Going beyond “black box” usage of AI tools, readers will understand why models work.3.     Enhances Problem-Solving Skills – By mastering calculus-driven optimization, readers can design new models and improve existing ones.4.     Supports Academic and Career Growth – Mastery of calculus strengthens research capabilities, technical interviews, and advanced study opportunities.5.     Encourages Critical Thinking – Rather than rote memorization, the book fosters curiosity about the connections between mathematics and intelligent systems. The Long-Term VisionArtificial Intelligence is not just a passing trend—it is shaping the future of science, technology, and human society. Calculus, as a timeless branch of mathematics, ensures that learners have the intellectual tools to adapt to new paradigms. As AI expands into quantum computing, neuroscience-inspired architectures, and beyond, the reliance on calculus will remain unshaken.This book provides readers not just with knowledge, but with intellectual independence—the ability to reason about algorithms, derive insights, and innovate confidently.   

A complete foundation for Statistics, also serving as a foundation for Data Science, that introduces inference using randomization and simulation while covering traditional methods. Leanpub revenue supports OpenIntro, so we can provide free desk copies to teachers interested in using our books in the classroom. More resources: openintro.org.

A deep dive into advanced integration techniques used in mathematical olympiads and integration competitions, with clear explanations and fully worked solutions.

An introduction to actor-critic algorithms as dynamical systems: featuring hand-computable examples, fast-slow reductions, and machine-checked Lean 4 proofs

Basic concepts of Real Analysis, suitable for someone with a knowledge of single-variable calculus and proof writing.

Google engineers are regular expression masters. Do you want to become one, too? The Smartest Way to Learn Python Regex transforms you into a regular expression master. The book leverages an innovative learning approach: (1) read a chapter, (2) watch a course video, and (3) solve a code puzzle. It's fun!

Behind every secure network lies an unbreakable mathematical truth. 'The Guardian Algorithms' bridges the gap between pure mathematics and cutting-edge cyber defense. Step into the mind of a digital architect.