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  1. Practical MCP: A Python Developer's Guide
    Practical MCP: A Python Developer's Guide
    From Theory to Production: Building and Deploying AI Tools for LLMs
    Arjuna Sky Kok

    Large Language Models are powerful, but they're trapped. They can't access real-time data, call APIs, or even count characters reliably. *Practical MCP* is your guide to setting them free. Learn the Model Context Protocol (MCP), the "USB-C for AI" that standardizes how LLMs connect to the outside world. This book teaches Python developers everything they need to build, secure, and deploy powerful AI tools. You'll master integrating with Claude, Gemini, and GPT; create interactive tools that ask for clarification; and automatically generate an MCP interface for any REST API. Go from a simple "Hello, World" to deploying a full-stack, multi-service AI application in the cloud. Stop hitting the LLM wall. Start building the solutions. This book shows you how.

  2. Aprende Python desde cero a experto

    Aprende todo sobre Python desde cero hasta experto. Curso para aprender Python paso a paso de forma fácil y con ejercicios prácticos que te ayuden a comprender todo sobre Python. El 100% del dinero recaudado con el libro será donado a @AmazonWatch, ONG que trabaja para proteger los bosques tropicales y los derechos de los pueblos indígenas.

  3. Clean Architectures in Python
    Clean Architectures in Python
    A practical approach to better software design
    Leonardo Giordani

    What is a good software architecture? Why should we bother structuring the code and spending time testing it? If you like spending hours debugging your programs or staying late at the office to recover from a buggy deploy in production this book is definitely NOT for you!

  4. Aprende Machine Learning en Español
    Aprende Machine Learning en Español
    Teoría + Práctica Python
    Juan Ignacio Bagnato

    Aprende los conceptos básicos del Machine Learning y avanza poco a poco con teoría y divertidos ejercicios prácticos en Python a niveles intermedios y avanzados hasta llegar al Deep Learning.Tu camino para convertirte en un Científico de Datos comienza aquí

  5. Python Made Simpler
    Python Made Simpler
    Nagachinmay K N

    Ever wished someone would explain coding like they’re talking to a friend?That’s exactly what Python – Made Simpler does. This beginner-friendly book teaches Python with the help of real-life analogies you already understand. Variables become jars in your kitchen. Loops feel like chores on repeat. And instead of just reading about code, you’ll actually write it—from day one. You don’t need any prior experience. You don’t need to be a tech wizard. You just need curiosity—and maybe a little love for coffee, because we talk about that too. Start learning Python the fun way—with simplicity, creativity, and confidence.

  6. QuantLib Python Cookbook
    QuantLib Python Cookbook
    Luigi Ballabio and Goutham Balaraman

    Quantitative finance in Python: a hands-on, interactive look at the QuantLib library through the use of Jupyter notebooks as working examples.

  7. Credit Risk Modeling Working Notes
    Credit Risk Modeling Working Notes
    A Collection of Presentations, Experiments, and Technical Papers
    Andrija Djurovic

    The Working Notes complement Applied Data Science for Credit Risk and Probability of Default Rating Modeling with R, offering practice-oriented insights. Based on the author’s GitHub repository, they address real-world challenges and are regularly updated to reflect ongoing developments.

  8. TLDR: Data Structures and Algorithms
    TLDR: Data Structures and Algorithms
    From Knowing Python to Cracking Leetcode Patterns
    John G

    A book designed to help you transition from merely knowing Python to cracking Leetcode patterns. This book explains core DSA concepts through clear, intuitive analogies and walks you through the most important Leetcode patterns. If you're aiming to ace your next coding interview, this is the book I wish I had when I started.

  9. A Quick Steep Climb Up Linear Algebra
    A Quick Steep Climb Up Linear Algebra
    Version 1.1.0
    Stephen Davies
    No Description Available
  10. MOST COMMON MISTAKES IN MACHINE LEARNING AND HOW TO AVOID THEM: With Examples in Python

    Understanding the most common mistakes in machine learning will allow you not only to avoid them, but to build better machine learning systems and less prone to errors. After reading this book, you will be ready to build more robust and trustworthy machine learning models.

  11. High School Python - Textbook
    No Description Available
  12. Python For Everyday, Everyone, Everywhere

    Ideas for projects when teaching Python as well as general inspiration ex. when building a hobby project. It sources use-cases from Reddit and is grouped in some 20 chapters.

  13. Beginner's Python Cheat Sheets

    Cheat sheets can be a really helpful resource when you're learning a new language. They remind you of the syntax and concepts you've just learned, so you can focus on writing your own code instead of rereading sections of a book or rewatching parts of a video.

  14. Mastering PyTorch and Lightning
    Mastering PyTorch and Lightning
    A Step-by-Step Practical Guide with QA
    Aghiles Kebaili

    Master deep learning with PyTorch & Lightning. Core concepts, practical Q&A, and production-ready code with a full companion GitHub repository.

  15. PyQuest 1000
    PyQuest 1000
    Code, Concepts & Cards
    Total Pythoneereing

    PyQuest 1000 provides a rapid, no-nonsense path to personalized Python mastery. Targeting entry-level topics this book reviews core concepts to help prepare you for interviews. PyQuest Flash Cards can also be used as a game or as a fast refresher to restore programming confidence. By building your own custom PyQuest deck you can enjoy an uncommon quick-review guaranteed to help you succeed!