Books

As an engineering leader, you will never get to the bottom of the list by working faster. Learn to lead your team as a single system across product, engineering, and people.

Master distributed systems through visual diagrams — from clock drift and CAP to Paxos, Raft, and distributed transactions, explained with clear illustrations instead of dense academic papers.

The Few Simple Ideas Behind Every Object Oriented Pattern and Principle.

All new language and library features of C++20 (for those who know previous C++ versions) The book presents all new language and library features of C++20. Learn how this impacts day-to-day programming, to benefit in practice, to combine new features, and to avoid all new traps. Buy early, pay less, free updates Other books:C++23C++17C++ Move Semantics

This book aims to be the comprehensive manual for type-level programming. It's about getting you from here to there---from a competent Haskell programmer to one who convinces the compiler to do their work for them.

SCRUM for HARDWAREを生み出した男達の物語：本書はWikispeedの誕生から最初のScrum for Hardware Gathering、Agile Product Charter、そしてScrum@Scaleに至るストーリー、そしてSCRUM for HARDWAREのメソッド、ケーススタディ、3つのパートに分かれています。本書の売上の50%が、WIKISPEEDプロジェクトをサポートするために寄付されます。英語版もあります。

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.

Mastering Advanced Time Series Forecasting in Python is the definitive sequel to the #1 forecasting bestseller. Designed for practitioners who want to go beyond ARIMA and basic ML, this book takes you deep into probabilistic forecasting, hierarchical coherence, and cutting-edge foundation models—backed by production-ready Python code. Learn how to assess forecastability, build scalable pipelines, quantify uncertainty, and deploy systems that deliver real business impact. Written by a globally recognized expert whose methods power multimillion-dollar decisions, this is the practical, honest, and advanced guide every data scientist, ML engineer, and quantitative professional needs to master modern forecasting.

Includes Editions 1, 2, 3, and 4. Editions 1-3 are listed under "Extras" after checking out, including for $0 purchases. AHSS provides a thorough intro to statistics and supports students preparing for the AP Statistics exam. B&W paperbacks (color) are sold for $25 ($40). Paperback royalties are shared between OpenIntro and the authors. Leanpub contributions go to authors to fund their time.

Learn databases from the bottom up by coding your own, in small steps, and with simple Go code (language agnostic).Atomicity & durability. A DB is more than files!Persist data with fsync.Crash recovery.KV store based on B-tree.Disk-based data structures.Space management with a free list.Relational DB on top of KV.Learn how tables and indexes are related to B-trees.SQL-like query language; parser & interpreter.Concurrent transactions with copy-on-write data structures.

macOS powers millions of devices, but few developers ever explore what lies beneath its polished interface. Inside macOS explains how the XNU kernel, Mach, BSD, Apple Silicon, APFS, and modern security technologies work together, giving systems programmers, security researchers, and engineers a deep understanding of Apple's operating system.

Revised for PyTorch 2.x! In 2019, I published a PyTorch tutorial on Towards Data Science and I was amazed by the reaction from the readers! Their feedback motivated me to write this book to help beginners start their journey into Deep Learning and PyTorch. I hope you enjoy reading this book as much as I enjoy writing it.

AI is an amplifier. It magnifies whatever engineering discipline — or lack of it — already exists, which means the bottleneck was never AI's capability; it is the collaboration space you design around it. This book is a six-level progression from early AI panic to sovereign engineering: the discipline of designing the environment in which human and artificial intelligence produce work worth keeping. It moves past prompting into the practices that compound — verification, habitat engineering, specification-first development, and the platform discipline that scales the practice across teams. The habitat is yours to design. Let's build it well.

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.

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