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Andreas Mueller Dec 09, 2020

I've been impressed by the wide overview of the book, which really spans the gamut of what AI means, from classification to search algorithms and A/B testing. The book focuses on some standard tools but also branches out to surface some lesser known libraries that can come in handy.While 468 pages can only give a taste of each topic, the book is jam-packed with examples and serves as a good starting point with plenty of references.

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Murphy Choy Aug 26, 2021

The book is a great recipe book for folks who want quick results without going through reams of content. I love the easy to read structure of this book.

Amazon Customer Mar 21, 2021

This is a great book, I believe there is something new and useful to you no matter how good you are at maching learning.For beginners, the topics for each part are very clear and well organized. The book will introduce the type of the problem it's going to talk about, the models useful to solve these problems, math and statistics behind the methods. All of these are presented with examples and step by step analysis and visualization, give you a step-by-step instruction for a maching learning project.For ML practitioners who want to learn new topics, like entering NLP, CV, RL or time series, you can find the chapters useful for you easily in the table of content. Just follow the codes and learn the concepts and you are good to read the papers with a good knowledge of how to write general codes in the area.For researchers, you can find some good engineering tricks, from using jupyter notebook more efficiently to some good modules to improve your code efficiency.And for those who have already learned how to do all above, this book has a good writing style with excellent structure for you to learn~

Isaac Dec 03, 2020

There are a number of survey books on the market for doing AI with python. I own many of them. Auffarth's approach here is unique in that it takes a do then explain the approach. The chapters are well structured with cookbook examples followed by in-depth explanations. What the author calls 'how to do it' then 'how it works.' The breath covered in the book is also impressive. everything from setting up a basic environment to deploying models into production. Applications range from typical deep learning stuff (like predicting housing prices) to image processing, audio applications, and fraud detection. This has become my latest 'go-to' book when I want to explore a new AI topic. I would recommend it to any data scientist looking to take their skills to the next level.

Eric D. Weber Apr 26, 2021

This book has the right mixture of breadth and depth, which is extremely challenging in the (growing) group of AI literature. What I enjoy the most is that you can both learn a lot of Python and/or learn a lot about ML and Experimentation, depending on your focus. Maybe most important, it allows those newer or intermediate in the field to scale up quickly. For beginners and practitioners, there is a lot of value to be found in the 400+ pages.

Artificial Intelligence with Python Cookbook: Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6

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Artificial Intelligence with Python Cookbook: Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6

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