Books

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.

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!

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

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.

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.

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.

This book is a quick foray into the world of deep learning-based computer vision and abnormal equipment sound detection. The readers are introduced to the ease with which powerful equipment and product quality monitoring solutions can be built using sound and visual data.

if you've read my chapter on naming in a famous software book (first or second edition) you may want to go a little deeper. Same author, same topic, all-new content!

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.

Essential Python libraries and frameworks that every aspiring data scientist, ML engineer, and Python developer should know.

This short book will tell you all you need to know to understand first-class citizenship in Python, which is the gateway to grasp how decorators work and how functional programming can supercharge your code.

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.

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.

Learn to Think Like a Senior Engineer — by Building a Card Game EngineA hands-on guide to system design, clean architecture, and engineering judgment. No fluff. Just practical, test-driven code you’ll actually use.

Unlock the power of geospatial data with Python! This hands-on guide is designed for beginners and intermediate users eager to explore spatial analysis and interactive mapping using open-source tools. You'll learn how to work with real-world data through practical examples and build skills in Python programming, vector and raster analysis, web mapping, and cloud computing. Whether you're a student, researcher, GIS professional, or data scientist, this book will equip you with the tools to tackle geospatial challenges with confidence. Color-print copies are available through Amazon.