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I bought three AI books this year and I ended up reading this one so far by Aurelien instead of the other (which was unfortunately in black & white, had misaligned paper cut, etc.). The book by Aurelien Geron (3rd edition) has better explanation, better visual aids, nicer print, etc.
One thing I probably would suggest though, is to maybe do a similar code comments style/explanation like what was done in the third book that I got (Deep Learning With Python by Francis Chollet), which I just got but haven't read yet. Some of the code explanation is on the same page/area/line. Convenient. No flipping of pages...
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From the brand
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Machine Learning, AI & more
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Machine Learning
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Artificial Intelligence
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Deep Learning
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Language Processing (NLP, LLM)
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Sharing the knowledge of experts
O'Reilly's mission is to change the world by sharing the knowledge of innovators. For over 40 years, we've inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.
Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.
From the Publisher
Prerequisites
This book assumes that you have some Python programming experience and that you are familiar with Python’s main scientific libraries, in particular NumPy, Pandas, and Matplotlib.
Also, if you care about what’s under the hood, you should have a reasonable understanding of college-level math as well (calculus, linear algebra, probabilities, and statistics).
About this Book
Machine Learning in Your Projects
So, naturally you are excited about Machine Learning and would love to join the party! Perhaps you'd like to give your homemade robot a brain of its own? Make it recognize faces? Or learn to walk around? Or maybe your company has tons of data (user logs, financial data, production data, machine sensor data, hotline stats, HR reports, etc.), and more than likely you could unearth some hidden gems if you just knew where to look. With Machine Learning, you can accomplish the following & much more:
- Segment customers and find the best marketing strategy for each group.
- Recommend products for each client based on what similar clients bought.
- Detect which transactions are likely to be fraudulent.
- Forecast next year’s revenue.
Objective and Approach
This book assumes that you know close to nothing about Machine Learning. Its goal is to give you the concepts, tools, and intuition you need to implement programs capable of learning from data.
We will cover a large number of techniques, from the simplest and most commonly used (such as Linear Regression) to some of the Deep Learning techniques that regularly win competitions. For this, we will be using production-ready Python frameworks:
- Scikit-Learn is very easy to use, yet it implements many Machine Learning algorithms efficiently, so it makes for a great entry point to learning Machine Learning.
- TensorFlow is a more complex library for distributed numerical computation. It makes it possible to train and run very large neural networks efficiently by distributing the computations across potentially hundreds of multi-GPU (graphics processing unit) servers. TensorFlow (TF) was created at Google and supports many of its large-scale Machine Learning applications.
- Keras is a high-level Deep Learning API that makes it very simple to train and run neural networks. Keras comes bundled with TensorFlow, and it relies on TensorFlow for all the intensive computations.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
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Hands-On Machine Learning with Scikit-Learn and PyTorch
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|---|---|---|
| Libraries covered | Scikit-Learn, Keras, and TensorFlow | Scikit-Learn and PyTorch |
About the author
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Customers say
Customers find this machine learning book thorough and easy to understand. They appreciate its writing style, with one customer noting it provides a well-written summary of algorithms.
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50 customers mention content, 43 positive, 7 negative
Great book if you are interested in learning Machine Learning for the first time. You only need some familiarity woth python.Read more
Good book.Read more
Excellent book for beginners! Easy to follow with complete practice data and codeRead more
Amazing Book. I'm learning a lot from this and found solutions for multiple of my project by reading the required articles from this book....Read more
9 customers mention readability, 7 positive, 2 negative
Excellent book for beginners! Easy to follow with complete practice data and codeRead more
...it's a great book, explains in detail, adds references and makes it easy to follow.Read more
...and explains the history of how we got there so it was fairly easy for me to follow and understand majority of the book....Read more
...n't rate it 5 stars was because it can get very word-heavy and confusing at times, but if you're willing to reread sections, there is some great...Read more
7 customers mention writing style, 5 positive, 2 negative
Great book, well written as if you are in a classroomRead more
Wow! What a thorough and well written book. It starts out with examples if you are purely interested in how to apply ML methods....Read more
...It's too much, too fast, too verbose, and poorly written....Read more
The content in this book is fantastic. I like the writing style, making it more enjoyable to read....Read more
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JeanReviewed in Brazil on January 19, 2025
Ótimo livro
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Bom material e conteúdo muito enriquecedorJeanÓtimo livro
Reviewed in Brazil on January 19, 2025
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- KlasReviewed in Sweden on February 18, 2025
Low quality of the paper. Text from the other side shines through.
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KlasLow quality of the paper. Text from the other side shines through.
Reviewed in Sweden on February 18, 2025
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- Saiyudh MannanReviewed in Germany on March 1, 2026
No review needed
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MarkignoReviewed in Italy on August 26, 2025
Manuale pratico e con un approccio moderno
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