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Write elegant Python code

The β€œPydon'ts – Write elegant Python code” book is a compilation of all the β€œPydon't” articles available here. The book will guide you through the core Python language, showing you how to use every single feature to write better, more elegant Python programs.

Each chapter of the book guides you through a specific feature of the Python language, teaching you how to use it and then showing you good example usages of that feature with examples of real Python code: some times you even get to dive into the code that implements the Python Standard Library.

This book is for beginners and advanced users alike, as it covers a wide range of Python features, so everyone has something to learn from the contents of this book.


β€œ[The book] seems to be extremely well put together, unlike some other books on Python I've read recently. It's a good book. I like how to the point it is.” ― Tanner S., USA.

β€œFirst of all, thank you thank you and thank you again for a beautiful ebook with such amazing content. If you're a beginner or a more experienced pythonista, pydon'ts will still achieve its purpose. Beautifully designed and explained! Definitely worth the reading. I'm reading it once more in a year or so!” ― Alonso, Mexico.

Neural Networks Fundamentals with Python

Ever wondered what a neural network really is, how it works, or how to implement one? Well, I did, and that is why I tried implementing one. And I failed. Some years later, I tried again, and it worked! And it was amazing! Now, I just want to help you do it yourself, so that you can take a peek behind the curtains of this world of machine learning, deep learning, and all those buzzwords.

In this short book, I will take you through the journey of implementing a neural network from scratch, and then we will use these networks you created to perform machine learning tasks. We will also play around with them and do all sorts of really interesting machine learning and deep learning experiments.

The book explains you the things that are needed, step-by-step, and gives you a reference implementation that you can find on GitHub.

By the time you are done with the book, you will have at your disposal a simple neural network framework that actually works, and that you have already used to explore interesting concepts from the worlds of machine learning and deep learning.

By the way, if you are unsure whether or not this book is for you, you can always read its chapters for free on my blog.