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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 3rd Edition

by Aurélien Géron (Author)
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Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started.

  • Use Scikit-learn to track an example ML project end to end
  • Explore several models, including support vector machines, decision trees, random forests, and ensemble methods
  • Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection
  • Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers
  • Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning

Read more
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  1. ISBN-10
    1098125975
  2. ISBN-13
    978-1098125974
  3. Edition
    3rd
  4. Publisher
    O'Reilly Media
  5. Publication date
    November 8, 2022
  6. Language
    English
  7. Dimensions
    7.25 x 2 x 9.5 inches
  8. Print length
    861 pages
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From the Publisher

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

HOML
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.
Aurélien Géron Machine Learning

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
Hands-On Machine Learning with Scikit-Learn and PyTorch
Libraries covered Scikit-Learn, Keras, and TensorFlow Scikit-Learn and PyTorch

Editorial Reviews

About the Author

Aurélien Géron is a Machine Learning consultant. A former Googler, he led YouTube's video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, a telecom consulting firm.

Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Société Générale), defense (Canada’s DOD), and healthcare (blood transfusion). He published a few technical books (on C++, WiFi, and Internet architectures), and was a Computer Science lecturer in a French engineering school.

A few fun facts: he taught his 3 children to count in binary with their fingers (up to 1023), he studied microbiology and evolutionary genetics before going into software engineering, and his parachute didn’t open on the 2nd jump.

Product details

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Aurélien Géron

Aurélien Géron

Brief content visible, double tap to read full content.
Full content visible, double tap to read brief content.

Aurélien Géron is a Machine Learning consultant. A former Googler, he led the YouTube video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, the firm that now manages the electric car sharing service Autolib'.

Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Société Générale), defense (Canada's DOD), and healthcare (blood transfusion). He published a few technical books (on C++, WiFi, and Internet architectures), and was a Computer Science lecturer in a French engineering school.

A few fun facts: he taught his 3 children to count in binary with their fingers (up to 1023), he studied microbiology and evolutionary genetics before going into software engineering, and his parachute didn't open on the 2nd jump.

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Customer reviews

4.7 out of 5 stars
774 global ratings

Customers say

Customers find this machine learning book thorough and comprehensive, particularly suitable for beginners in supervised learning. The writing style is well-received, and customers say it makes learning enjoyable and interesting. However, the language receives mixed feedback, with one customer noting it can be very word-heavy.

Select to learn more

Knowledge levelWriting styleBook detailEnjoymentEase of understandingLanguage
20 customers mention "Knowledge level"19 positive1 negative

Customers appreciate the book's knowledge level, finding it comprehensive and thorough, particularly as an introductory guide to supervised machine learning.

"A comprehensive book, with in-depth coverage and great graphics of many relevant topics. I wish the editors made it easier to read...." Read more

"Nothing else to add, it's a great book, explains in detail, adds references and makes it easy to follow." Read more

"This book is full of great information but is entirely worthless for anyone actually trying to learn and not decorate a bookshelf...." Read more

"Love the book. Very educational, combines explanations with live programs...." Read more

5 customers mention "Writing style"4 positive1 negative

Customers appreciate the writing style of the book, with one mentioning it provides a well-written summary of machine learning algorithms.

"Great book, well written as if you are in a classroom" Read 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

"Well written summary of ml algorithms , along with a collection of example Jupyter notebooks...." Read more

"...Sentences are ambiguous and the style is not concise, often leading me to seek outside sources for clarity." Read more

3 customers mention "Book detail"3 positive0 negative

Customers appreciate the book's detailed content, with one mentioning it provides the best summary of machine learning concepts.

"...Book goes into the detail 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

"...background is in mechanical engineering and I find the detail of the book to be satisfying, without getting so bogged down in theory and proofs as..." Read more

"...This is the best summary of ML I have ever read, combining theory with practice. Be very careful of the seller...." Read more

3 customers mention "Enjoyment"3 positive0 negative

Customers find the book enjoyable and fun to read, with one mentioning they are reading it cover-to-cover.

"Super interesting book if you are into ML" Read more

"Interesting and make learning fun with colorful example figures" Read more

"...as they come up in your work/learning, but I am actually enjoying reading it cover-to-cover to broaden my understanding of the subject...." Read more

6 customers mention "Ease of understanding"4 positive2 negative

Customers have mixed experiences with the book's clarity, with some finding it easier to understand while others report it being difficult to read.

"...it's a great book, explains in detail, adds references and makes it easy to follow." 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

"...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

"Explains concepts in simple language. Machine language can be very complex but this book makes it easier to understand." Read more

3 customers mention "Language"0 positive3 negative

Customers find the language of the book complex and word-heavy, with one customer noting that sentences are ambiguous.

"...I wish the editors made it easier to read. Sentences are ambiguous and the style is not concise, often leading me to seek outside sources for..." Read more

"...The only reason I didn'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,..." Read more

"Explains concepts in simple language. Machine language can be very complex but this book makes it easier to understand." Read more

Good book.
5 out of 5 stars
Good book.
The book very well printed and I received ina good conditions.
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Top reviews from the United States

  • Amazon Customer
    5.0 out of 5 stars Great book to learn practical Machine Learning
    Reviewed in the United States on April 4, 2025
    Format: KindleVerified Purchase
    I have just finished Hands-On ML book and I cannot recommend it enough.

    I have been working as a Mobile Software Developer for 12 years and now I am thinking about trying something new. I remember some Math and Statistics from school but definitely not enough to get deep into the subject.

    From my experience, you can read the book and finish all the exercises without understanding any of the Math (although as author points out, it is beneficial if you understand the Math behind it - e.g. to understand why it works, read and implement papers).

    Book goes into the detail and explains the history of how we got there so it was fairly easy for me to follow and understand majority of the book. I missed this kind of detail from ML courses that I tried. You will also see significant papers explained - something that would be difficult for me to do alone at this point.

    However, one thing I appreciated the most were the exercises. In ML courses I tried, the exercises were simple and too easy to give you anything. Here it was a real challenge and I have a good feeling about what I learned by doing those exercises.

    There are also a lot of references for books or papers in case you want to focus on a specific area.

    One blind spot I am seeing though is focus on Keras/TensorFlow and GCP pipeline whereas the most examples on internet seem to be from PyTorch and AWS as a most popular cloud solution. However, as author points out, if you know one it will be easy for you to switch (I also reimplemented some of the PyTorch projects as part of exercises without too much difficulty). Still, I need to think about it and get some more PyTorch and AWS experience.
    9 people found this helpful
    Helpful
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  • David Alejandro Rodríguez Fernández
    5.0 out of 5 stars Good book
    Reviewed in the United States on August 28, 2025
    Format: PaperbackVerified Purchase
    It's a very good introductory book to supervised and unsupervised learning algorithms. It has a lot of code and brief explanations of the theory. It's a very good start if you want to venture into the world of machine learning.
    Helpful
     Report
  • Diego
    5.0 out of 5 stars Hands on experience machine learning review
    Reviewed in the United States on July 25, 2025
    Format: PaperbackVerified Purchase
    Excellence content and print quality, strong fundamentals to understand machine learning concepts with practice
    Helpful
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  • Atul Deshmukh
    5.0 out of 5 stars Nice
    Reviewed in the United States on October 30, 2025
    Format: PaperbackVerified Purchase
    Delivery and book perfect
    Helpful
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  • DalasCustomer
    4.0 out of 5 stars Really good book, inadequate packaging by Amazon
    Reviewed in the United States on June 11, 2025
    Format: PaperbackVerified Purchase
    Amazon packages the book inside a box without any inner cushioning or envelope. It arrived with a bent corner and tiny bruises. That aside the book is ok.
    Customer image
    DalasCustomer
    4.0 out of 5 stars
    Really good book, inadequate packaging by Amazon

    Reviewed in the United States on June 11, 2025
    Amazon packages the book inside a box without any inner cushioning or envelope. It arrived with a bent corner and tiny bruises. That aside the book is ok.
    Images in this review
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    One person found this helpful
    Helpful
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  • Louie
    5.0 out of 5 stars This is a dynamite book for practical understanding.
    Reviewed in the United States on October 4, 2023
    Format: PaperbackVerified Purchase
    Wow! What a thorough and well written book. It starts out with examples if you are purely interested in how to apply ML methods. The rest of the book takes a deeper dive into what the different algorithms are doing and gives examples of how to apply each method. I think the level of the writing is a great balance between thoroughness and approachability. My background is in mechanical engineering and I find the detail of the book to be satisfying, without getting so bogged down in theory and proofs as to make it overwhelming. It is also very comprehensive - you could use this book as a reference for looking up more detail about specific algorithms as they come up in your work/learning, but I am actually enjoying reading it cover-to-cover to broaden my understanding of the subject.
    Finally, you can't beat the price for a book of this quality. This well exceeded my expectations.
    12 people found this helpful
    Helpful
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  • VINCENT NSENGIMANA
    5.0 out of 5 stars Only for Experts |Econometricians can transform the whole world through reading this amazing book
    Reviewed in the United States on August 29, 2025
    Format: PaperbackVerified Purchase
    This book is the best one I have been looking for in my career development. I appreciate your quick service delivery, and I thank the Author for the tough work they have done with us.
    However, the cost of transport is so challenging (from the AMAZON/USA to Africa/Ghana is so expensive), and the book cover page would be a hard one instead of a paper cover, as the book is heavier.

    Thank you.
    Helpful
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  • tb
    5.0 out of 5 stars Good book
    Reviewed in the United States on October 6, 2025
    Format: PaperbackVerified Purchase
    Really good book to own.
    Helpful
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Top reviews from other countries

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  • Jean
    5.0 out of 5 stars Ótimo livro
    Reviewed in Brazil on January 19, 2025
    Format: PaperbackVerified Purchase
    Bom material e conteúdo muito enriquecedor
    Customer image
    Jean
    5.0 out of 5 stars
    Ótimo livro

    Reviewed in Brazil on January 19, 2025
    Bom material e conteúdo muito enriquecedor
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  • Klas
    1.0 out of 5 stars Low quality of the paper. Text from the other side shines through.
    Reviewed in Sweden on February 18, 2025
    Format: PaperbackVerified Purchase
     
    Customer image
    Klas
    1.0 out of 5 stars
    Low quality of the paper. Text from the other side shines through.

    Reviewed in Sweden on February 18, 2025

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  • Joshua
    5.0 out of 5 stars Great read!
    Reviewed in Japan on December 5, 2024
    Format: PaperbackVerified Purchase
    plenty of detail on all topics. Quite heavy and bulky so try not to have to take it places too much to avoid damaging it or your back lol
    Report
  • Markigno
    5.0 out of 5 stars Manuale pratico e con un approccio moderno
    Reviewed in Italy on August 26, 2025
    Format: PaperbackVerified Purchase
    Ottimo libro per chi vuole padroneggiare il machine learning e il deep learning in modo pratico. Gli esempi con scikit-learn aiutano a capire bene i concetti di base, mentre le parti su Keras e TensorFlow mostrano come costruire e addestrare reti neurali anche complesse. L’autore riesce a spiegare con chiarezza temi tecnici come regularization, ottimizzazione e reti convoluzionali, senza mai risultare pesante. Una guida aggiornata, solida e ricca di codice, perfetta per chi lavora già con Python e vuole applicare davvero le tecniche di AI nei propri progetti.
    Report
  • Cristina Gonzalez Marrero
    5.0 out of 5 stars Best book!
    Reviewed in the United Kingdom on October 5, 2025
    Format: PaperbackVerified Purchase
    Absolutely brilliant!
    Report