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  1. Mastering CatBoost: The Hidden Gem of Tabular AI
    Mastering CatBoost: The Hidden Gem of Tabular AI
    Harness the Power of CatBoost for Tabular Data and Beyond
    Valery Manokhin

    Unlock the full potential of CatBoost — a powerful gradient boosting library built for structured/tabular data and still underused in practice.In Mastering CatBoost: The Hidden Gem of Tabular AI, you’ll learn how to take advantage of CatBoost’s key strengths: native categorical feature handlingstrong accuracy, and fast inference — without brittle preprocessing pipelines.Written for data scientists, ML engineers, and applied researchers, the book covers:Real-world use cases and end-to-end workflowsPractical tuning strategies and diagnosticsInterpretability with SHAP, feature importance, and constraintsDeployment-minded best practices and common failure modesWhether you’re new to CatBoost or ready to go deeper, this is a clear, practical guide to building high-performance tabular models.Early Access is available now, with ongoing updates leading to the full release in 2026.

  2. 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.

  3. Django 6 Cookbook, Second Edition
    Django 6 Cookbook, Second Edition
    Build modern full-stack apps with Django 6, Python 3.12, APIs, authentication, testing, search, and deployment
    GitforGits | Asian Publishing House

    The recipes in this book are practical answers to the kind of problems that real Django applications encounter, sometimes on the first day of a project and sometimes deep into the life of a codebase that has grown well beyond its original design. This book is written to guide you to utilize Django 6.0 capabilities in your apps with ease of implementation.

  4. LLM Quantization
    LLM Quantization
    From the Bits Up
    Hatem M.

    Anyone can run INT4 and read off the accuracy drop. This book explains why that number is what it is — building every quantization method from scratch, breaking it on purpose, and measuring the result. Quantization, from the bits up.

  5. Simplifying Machine Learning with PyCaret
    Simplifying Machine Learning with PyCaret
    A Low-code Approach for Beginners and Experts!
    Giannis Tolios

    A beginner-friendly introduction to machine learning with Python, that is based on the PyCaret and Streamlit libraries. Readers will delve into the fascinating world of artificial intelligence, by easily training and deploying their ML models!

  6. Feature Selection in Machine Learning
    Feature Selection in Machine Learning
    Over 20 methods to select the most predictive features and build simpler, faster, and more reliable machine learning models.
    Soledad Galli, PhD

    Learn how to implement various feature selection methods in a few lines of code and train faster, simpler, and more reliable machine learning models. Using Python open-source libraries, you will learn how to find the most predictive features from your data through filter, wrapper, embedded, and additional feature selection methods.

  7. From Source Code To Machine Code
    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.

  8. The Modern Guide to AI-Powered Web Scraping and Automation
    The Modern Guide to AI-Powered Web Scraping and Automation
    Hands-On Strategies for Stealth, Structured, and AI-Driven Web Scraping
    Wasi

    Discover how modern web scraping goes beyond simple scripts. Learn to extract, automate, and transform data from dynamic websites using Python, Playwright, undetected-chromedriver, Chrome DevTools MCP, and AI tools. Packed with hands-on examples and expert tips, this book shows you how to build ethical, scalable, and intelligent scraping workflows that turn raw web content into actionable insights.

  9. Applied Data Science for Credit Risk
    Applied Data Science for Credit Risk
    A Practical Guide in R and Python
    Andrija Djurovic

    This book provides a practical guide to critical data science methods, focusing on their application in credit risk management. Using examples in R and Python, it presents step-by-step processes for applying various analytical techniques while highlighting the importance of aligning methods with the specific characteristics of the data. Designed for practitioners and those with foundational data science and banking knowledge, the book bridges theory and practice with real-world examples.

  10. Interpreting Machine Learning Models With SHAP
    Interpreting Machine Learning Models With SHAP
    A Guide With Python Examples And Theory On Shapley Values
    Christoph Molnar

    Master machine learning interpretability with this comprehensive guide to SHAP – your tool to communicating model insights and building trust in all your machine learning applications.

  11. Build Your Own Coding Agent
    Build Your Own Coding Agent
    The Zero-Magic Guide to AI Agents in Pure Python
    J. Owen

    Skip the black-box frameworks. Build a production-grade AI coding agent from scratch in pure Python - cloud or local, tested with pytest, all in a single file.

  12. Computer graphics in Python
    Computer graphics in Python
    Advanced vector graphics using Pycairo and Python
    Martin McBride

    Pycairo is a great library for creating high quality vector graphics in Python. This book covers the full features of the library in detail, with practical code examples and illustrations, from an author with many years experience in computer graphics software.

  13. Mastering Regular Expressions
    Mastering Regular Expressions
    A Complete Guide for Developers Across Languages and Platforms
    Steve Publications

    Regex doesn't have to feel like cryptic punctuation. Mastering Regular Expressions shows you how patterns really work, how to debug them when they don't and how to use them confidently across nine programming languages. Go beyond memorizing syntax and learn to write regex that's clear, efficient and portable.

  14. Server Automation with Python: The 2026 Edition
    Server Automation with Python: The 2026 Edition
    Modern Infrastructure Workflows for Cloud-Native, AI-Augmented, and Immutable Systems
    Steve Publications

    Infrastructure automation in 2026 is about building intelligent, resilient, and cloud-native systems at scale. Server Automation with Python: The 2026 Edition explores modern Python-driven workflows spanning GitOps, immutable infrastructure, cloud SDKs, chaos engineering, and AI-assisted development, providing practical guidance for creating secure, scalable, and self-healing platforms.

  15. A QuantLib Guide
    A QuantLib Guide
    An introduction to the usage of the QuantLib library
    Luigi Ballabio
    No Description Available