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Computer Science

  1. Mastering STM32 - Second Edition
    Mastering STM32 - Second Edition
    A step-by-step guide to the most complete ARM Cortex-M platform, using the official STM32Cube development environment
    Carmine Noviello

    With more than 1200 microcontrollers, STM32 is probably the most complete ARM Cortex-M platform on the market. This book aims to be the most complete guide around introducing the reader to this exciting MCU portfolio from ST Microelectronics and its official CubeHAL and STM32CubeIDE development environment.

  2. The Hundred-Page Language Models Book
    The Hundred-Page Language Models Book
    hands-on with PyTorch
    Andriy Burkov

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

  3. Certainty by Construction
    Certainty by Construction
    Software and Mathematics in Agda
    Sandy Maguire
    No Description Available
  4. The Hundred-Page Machine Learning Book

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

  5. Why We Still Suck At Resilience
    Why We Still Suck At Resilience
    Organizational Dynamics
    Adrian Hornsby

    Your organization does all the right things. They practice chaos engineering, GameDays, and load testing. They conduct incident reviews and operational readiness reviews. Yet the same types of incidents keep recurring. This book examines why resilience practices so often fail to build resilience, revealing the organizational dynamics that systematically transform learning mechanisms into compliance theater and what you can do to navigate them consciously.

  6. Mastering Advanced Time Series Forecasting in Python: Probabilistic, Hierarchical, and Foundation Models
    Mastering Advanced Time Series Forecasting in Python: Probabilistic, Hierarchical, and Foundation Models
    Master advanced forecasting with Python using machine learning, deep learning, and cutting-edge foundational models. Learn hierarchical and probabilistic forecasting, forecastability, metrics, and scalable pipelines. Build robust, real-world forecasting systems with production-ready code and expert guidance.
    Valery Manokhin

    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.

  7. Build Your Own Database in Go From Scratch
    Build Your Own Database in Go From Scratch
    From B+tree to SQL in 3000 lines
    build-your-own.org

    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.

  8. Super Study Guide: Algorithms & Data Structures
    Super Study Guide: Algorithms & Data Structures
    Afshine Amidi and Shervine Amidi

    A concise, illustrated guide to algorithms and data structures, perfect for coding interviews, classes, or self-study. Covers key concepts, from fundamentals to graphs, trees, sorting, and search techniques.

  9. Build Your Own Redis with C/C++
    Build Your Own Redis with C/C++
    Network programming, data structures, and low-level C.
    build-your-own.org

    Build real-world software by coding a Redis server from scratch.Network programming. The next level of programming is programming for multiple machines. Think HTTP servers, RPCs, databases, distributed systems.Data structures. Redis is the best example of applying data structures to real-world problems. Why stop at theoretical, textbook-level knowledge when you can learn from production software?Low-level C. C was, is, and will be widely used for systems programming and infrastructure software. It’s a gateway to many low-level projects.From scratch. A quote from Richard Feynman: “What I cannot create, I do not understand”. You should test your learning with real-world projects!

  10. Discrete Mathematics for Computer Science
    Discrete Mathematics for Computer Science
    Alexander S. Kulikov, Alexander Golovnev, Alexander Shen, Vladimir Podolskii, and Marie Brodsky

    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.

  11. Probabilistic Forecasting with Conformal Prediction in Python
    Probabilistic Forecasting with Conformal Prediction in Python
    The Practical Guide to Uncertainty Quantification for Data Science, Machine Learning, and Forecasting
    Valery Manokhin

    Turn uncertainty into a competitive advantage with probabilistic forecasting and Conformal Prediction.

  12. The GPG Guide
    The GPG Guide
    Modern OpenPGP for Every Workflow
    Tony Gies

    The comprehensive, current PGP and GnuPG reference: from air-gapped key generation to YubiKey provisioning, Git signing, email encryption, and emergency recovery. Can't afford it? I got you -- scroll to end of description

  13. Foundations of Computing
    Foundations of Computing
    An Accessible Introduction to Formal Languages
    Charles D. Allison

    An accessible, practical approach to formal languages with an introduction to computability.

  14. Thinking with Types
    Thinking with Types
    Type-Level Programming in Haskell
    Sandy Maguire

    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.

  15. Distributed Systems for practitioners

    Learn the basic principles that govern how distributed systems work and how you can design your systems for increased performance, availability and scalability. Understand the basic algorithms and protocols used to solve the most common problems in the space of distributed systems.