Books

Crack the really hard topics in Python once for all. And, yes, this book starts each chapter from scratch.

Learning about microcontrollers? Want to avoid the mistakes that I made along my learning journey? All the tips and tricks that will help you advance your skills, demonstrated using a Raspberry Pi Pico.

The sexiest job in the 21st century? Data Science!Coffee Break Pandas teaches you the new superpower of analyzing and processing data with Python's Pandas framework. If solving puzzles is fun for you, you'll love ❤ this book with 74 brand-new, hand-crafted Pandas puzzles to help you stay relevant in today's marketplace.

Once you’ve completed Part 1 and Part 2, you’ll be able to build nearly any project that you want, and deploy it for the world to use. If you’re stuck for ideas, you can go through the examples given in Part 3, which consists of practical tutorials to build everything from web scrapers to chat bots.

Fear of missing out on data science and machine learning?This ​eBook ​gives you a fun way to start learning data science with Python. ​It gives you a thorough introduction Python's most important library for data science: NumPy. 100% Based on puzzle-based learning - scientifically proven to generate ​44% better learning retention and ​efficiency.​

Raspberry Pi Computing: Gas Sensors aims to provide a full description of the process of setting up a Raspberry Pi computer to measure and record data from gas sensors. We'll look at different versions of the Pi, along with loading and configuring the software required with some basic Linux use.

Aprenda a construir modelos de simulação de eventos discretos e de simulação baseadas em agentes utilizando o SimPy, uma biblioteca da linguagem Python.

Raspberry Pi Computing: Analog Measurement aims to provide a full description of the process of setting up a Raspberry Pi computer to measure and record analog values using different sensors and an A to D converter. We'll look at different versions of the Pi, along with loading and configuring the software required with some basic Linux use.

A series on writing effective, idiomatic pandas.

Apprendre à programmer n'a jamais été aussi fun !

Python, JavaScript, and TypeScript taught side by side — every concept in all three languages, every example pulled from real QA work.

It's a practical book. We're going to build something real together, a University API, and we're going to grow it chapter by chapter until it looks like a system you'd be proud to deploy. We'll start with a few endpoints, give it databases, make it concurrent, lock it down with authentication, wrap it in containers, and finally split it into cooperating services that talk over the network.

We'll stick to five libraries, not because more would be a problem, but because keeping it simple shows how well we can organise things. When you download MNIST with just the standard library, you finally see what a dataset loader was hiding. If you write attention as four lines of NumPy before you ever call a PyTorch module, it's no longer a magic process but just plain arithmetic.

PyTorch Deep Dive is a practical guide to mastering modern deep learning with PyTorch. From core concepts to advanced topics like transformers, diffusion models, and production deployment, it combines clear explanations, hands-on examples, and real-world best practices to help you build and scale AI applications with confidence.