AI Crash Course: A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python

This book is fun, challenging, and entertaining. I would totally love it except for one minor thing. It is written in TensorFlow and PyTorch, so you really have to know both. Nevertheless, the book is good for a read and reread.

I am super-excited for my dear friend Hadelin for publishing his first book! I love my copy - it's got fantastic explanations and hands-on examples of AI applications. If you've taken any of our courses on Deep Learning and Artificial Intelligence, you will find this book a fantastic supplement to your learning journey. And if you're new to Hadelin's teaching method, you're in for a treat! This book will hold your hand as you venture into the world of AI, Reinforcement Learning, Q-Learning, Deep Convolutional Q-Learning and more. This book is build around real-world use-cases of AI: from advertising and energy savings to warehouse optimization and self-driving cars. The business applications is what really makes this book stand out. However, what I, perhaps, appreciate the most is that Hadelin gets you started from scratch. Artificial Intelligence libraries have gotten so easy to use that even with minimal knowledge of Python you can write up a few dozen lines of code - and voila! Have a Deep Neural Network ready to go. In this book Hadelin makes sure to supply you with that minimal Python foundation to get you going. In short - you're going to love this book, learn a lot and feel accomplished after every chapter! - Kirill

So far this book has been excellent (I'm currently on Ch6). It is a quick read, explaining the concepts well. I hope to have a first read through done by the end of the day. The author seems to have strong understanding of AI fundamentals, but can still explain in a way that a novice can understand. But..... All the graphs are in grey scale / black and white. This makes it very difficult to distinguish between the yellow, green and purple plots on a graph. Or which plot corresponds to which title in the key.

I really like this book, it is hands on using python

I don't know what a "crash course" should contain. I would only say that this book is narrowly focused. For a full treatment of AI see AI A Modern Approach by Russell and Norvig. Books like The Encyclopedia of Artificial Intelligence will also give you some idea of the 100 or so active AI subfields.

In AI Crash Course, Hadelin has capitalized on his years of experience teaching thousands of learners across the globe by taking the best of his MOOC content and converting it into a concise and engaging book format. Even if you have little or no experience coding in Python, Hadelin provides you with just enough of the basics to successfully implement the hands-on projects included in the book. Coupled with the use of Google's Colab environment, even novices can successfully complete the most sophisticated models included, with the end result being a working, shareable portfolio of real-world AI applications.

I'm really enjoying this book and learning quite a bit. The descriptions are excellent, as are the encouragements to try to figure things out on your own before being given the answer/solution. I definitely recommend this book.

I loved the examples on how to apply AI. Most of books focus on teaching the syntax but no how to apply it!!

I am surprised how this got published. On page 42 he is mentioning a formula for a distribution, before on page 48 (!) he tries to tell you what a distribution IS. He uses the word "magic", pretty much the last word I want to see in an AI book. He refers to COLORS in diagrams that are clearly printed in GRAYSCALE (e.g. p. 51). He starts with a Python course that leads nowhere because along the way, further Python concepts... and that is really how this feels, as an entire book: a series of scraps, chaotically scattered, in no logical sequence, full with deviations. The author has neither decided on the audience, nor on the content — is it for beginners, is it for experts, how much theoretical concepts, and when which (which mathematical, which algorithmic). I am sorry, but I cannot recommend this at all.

Tout est dans le titre. Les exemples sont tout autant complexes que concrets et très bien expliqués.

Beaucoup de techno ne sont plus d'actualité. Le code ne marche plus car certaines librairies ne sont plus disponibles. Dans l'ensemble, un livre intéressant. Mais il faut une bonne mise à jour.