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Category: "Computer Science"

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  1. Mastering Modern Time Series Forecasting
    A Comprehensive Guide to Statistical, Machine Learning, and Deep Learning Models in Python
    Valery Manokhin

    800 pages. 11 chapters. The full forecasting stack in Python — from ARIMA to foundation models — with production-grade code and proper evaluation. No hype.

  2. 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. 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.

  4. 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.

  5. 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.

  6. Architecting Agentic Systems
    Engineering Dependable AI Agents
    Damian Beresford

    You shipped the demo. The model worked. Now production is coming, and the demo is not a system. An agentic system is a distributed-systems engineering problem — the reliability lives in the shell, not the model.

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

  8. 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.

  9. Code a database in 45 steps (Go)
    a series of test-driven small coding puzzles
    Lowram Eepson

    This series of test-driven small coding puzzles lets you code a database from scratch (no dependencies).We'll cover KV storage engines, LSM-Tree indexes, SQL, concurrent transactions, ACID, etc.

  10. 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.

  11. From Source Code To Machine Code
    Build Your Own Compiler From Scratch
    build-your-own.org

    Build a compiler to learn how programming languages work. Use low-level assembly to learn how computers work. Walks through a minimal yet complete compiler. Compiles a static-typed language into x64 ELF executables.Simple interpreter.Bytecode compiler.x64 assembly & instruction encoding.Translate bytecode to x64 code.Generate binary executables.

  12. Understanding Kubernetes in a visual way
    Learn & Discover Kubernetes in sketchnotes - with some tips included -
    Aurélie Vache

    Understanding Kubernetes can be difficult or time-consuming. I've created this collection of sketchnotes about Kubernetes in order to explain the Cloud technology in a visual way.

  13. 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!

  14. Certainty by Construction
    Software and Mathematics in Agda
    Sandy Maguire
    No Description Available
  15. The foundation of all programs is organization of variables/functions into nested scopes. Yet, many never contemplate how & why these decisions are made and the impacts on code maintainability. Scope & Closures examines lexical scope, builds on its principles for the power of closure, and digs into the module pattern for better program structure.