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  1. The Mathematical Intuition Behind Deep Learning
    The Mathematical Intuition Behind Deep Learning
    From the Dot Product to Multivariate Calculus and the Jacobian, with Python
    Alex Punnen

    Stop treating neural networks as magic. Starting from a single dot product, this book derives every step to Backpropagation with Matrix Calculus, then turns the math into working Python. No frameworks, no skipped steps. Written for developers who want to know why the equations work, not just how to call them.

  2. Ansible For Linux by Examples
    Ansible For Linux by Examples
    200+ Automation Examples For Linux System Administrator and DevOps
    Luca Berton

    Many Linux System Administrators struggle with Ansible, I created a book that gives you copy-and-paste Playbook code and solves the most common errors that you could use to save time every day. 

  3. Vibe to First Sale: Vibecoding a Lean AI Business from $0 to $29

    Turn AI into leverage, engineer your first $29 sale, and prove your business is real - in days, not months.

  4. arc42-FAQ
    arc42-FAQ
    Pragmatic, real-world software architecture documentation
    Gernot Starke

    This book contains answers to the most common questions regarding arc42 - the pragmatic template for communicating software architectures.

  5. 70 Simple Songs for the 8-Note Tongue Drum Without Musical Notes

    The songbook includes very simple, popular children’s and folk songs. All 70 songs in this book have been written without using the classic music score system because it is for the absolute beginners who can not read sheet music. This book is aimed at those who want to add popular melodies to their experimentation.

  6. Introductory Statistics with Randomization and Simulation
    Introductory Statistics with Randomization and Simulation
    David Diez, Christopher Barr, Mine Cetinkaya-Rundel, and OpenIntro

    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.

  7. Production Engineering from DevOps to MLOps
    Production Engineering from DevOps to MLOps
    Sebastien Donadio and Arnab Bose

    The book to bridge DevOps and MLOps

  8. Kolban's book on ESP32

    The definitive guide to programming on the ESP32.

  9. AI Trading: The Uncomfortable Truth
    AI Trading: The Uncomfortable Truth
    Why AI Won't Make Most Traders Rich, and What It Can Still Do for You
    Julian Vellner

    AI can analyze a thousand charts in seconds. So why can't it reliably make you rich? Discover the uncomfortable truth about AI trading, the mistakes most people overlook, and what these powerful tools can actually do for you.

  10. DNS A Visual Guide
    DNS A Visual Guide
    Understand Name Resolution from First Lookup to Real World Operations
    Reiner Braun

    Understand DNS through clear visual explanations of name resolution, zones, records, caching, security, and practical operations.

  11. MCP A Visual Guide
    MCP A Visual Guide
    A Beginner-Friendly Foundation for Practical MCP Engineering
    Reiner Braun

    Understand how Model Context Protocol hosts, clients, and servers work together. Visual explanations introduce capabilities, message flows, transports, security boundaries, and reliable MCP engineering.

  12. MCP Apps for Claude
    MCP Apps for Claude
    Build interactive UI inside the conversation
    Sandeep Kumar Patel

    Build interactive apps inside Claude's conversations, from your first MCP tool to Claude's connector directory.

  13. The Agents.md Cookbook
    The Agents.md Cookbook
    Rules Files for AI Coding Agents
    Kristian Reformis

    Your AI coding agent starts every session knowing nothing about your project, so it guesses - and the guess is sometimes expensive. The AGENTS.md Cookbook shows you how to write short, specific rules files, how to test them with a simple before-and-after method, and includes twelve ready-to-adapt recipes for real project types, labeled honestly about what has and has not been tested.

  14. Python Testing with pytest A Practical Guide to Writing Reliable Tests
    Python Testing with pytest A Practical Guide to Writing Reliable Tests
    A Practical Guide to Writing Reliable Tests
    AhmedAdawy

    Turn Python testing from a manual chore into a reliable engineering workflow. Learn pytest through practical examples covering assertions, exceptions, fixtures, parametrization, test organization, coverage, and CI. Build a stronger safety net for your Python projects and refactor with confidence

  15. Closing the AI Gap
    Closing the AI Gap
    The Seven-Gap Implementation Guide for Enterprise AI Transformation — Companion to Mind the AI Gap
    Antoine Craske

    Most organizations know they have an AI problem. Few have the tools to diagnose it honestly, measure it rigorously, and close it systematically.