Scientific Books

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

Author: Aurélien Géron

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,...

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 best-selling book uses concrete examples, minimal theory, and production-ready Python...

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Description

Description

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 best-selling 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 Aurelien Geron 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.

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Specifications

Specifications

Author
Aurélien Géron
Publisher
O'Reilly Media
Type
Technology, Computers - Informatics, Artificial Intelligence
Language
English
Cover
Soft
Number of Pages
850
Release Date
11/2022
Publication Date
2022
Dimensions
17.7x23.3 cm
ISBN-13
9781098125974

Important information

Specifications are collected from official manufacturer websites. Please verify the specifications before proceeding with your final purchase. If you notice any problem you can report it here.

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Reviews (2)

Reviews

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  • tonimel
    5
    2 out of 2 members found this review helpful

    Verified purchase

    I'm somewhere in the middle so far. Simple English, excellent balance of detail without too much blah blah. It says exactly what is needed. In almost every chapter, it starts with a description for understanding, and then goes straight to code and how it is applied – don't forget, it's hands on. There is math in several places, but in some parts there isn't and it focuses more on intuitive understanding. With how many things exist on the internet, this isn't an issue in my opinion. It's more of a hands-on book, if you want to go deeper there are countless free resources. Python knowledge is required, so if you don't know it, taking a Python course before starting the book will help a lot (e.g. CS50p).

    Translated from Greek ·
    Did you find this review helpful?
    • Paper quality
    • Was it easy to read?
    • Understanding of the subject matter
    • Was it interesting enough?
    • I liked the writing style
    • I would read a book by the same author
    • I would recommend it for reading
  • I'm somewhere in the middle so far. Simple English, excellent balance of detail without too much blah blah. It says exactly what is needed. In almost every chapter, it starts with a description for understanding, and then goes straight to code and how it is applied – don't forget, it's hands on. There is math in several places, but in some parts there isn't and it focuses more on intuitive understanding. With how many things exist on the internet, this isn't an issue in my opinion. It's more of a hands-on book, if you want to go deeper there are countless free resources. Python knowledge is required, so if you don't know it, taking a Python course before starting the book will help a lot (e.g. CS50p).

    Translated from Greek ·
    2
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Description & Specifications

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 best-selling 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 Aurelien Geron 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.

Manufacturer

Author
Aurélien Géron
Publisher
O'Reilly Media
Type
Technology, Computers - Informatics, Artificial Intelligence
Language
English
Cover
Soft
Number of Pages
850
Release Date
11/2022
Publication Date
2022
Dimensions
17.7x23.3 cm
ISBN-13
9781098125974

Important information

Specifications are collected from official manufacturer websites. Please verify the specifications before proceeding with your final purchase. If you notice any problem you can report it here.

Reviews (2)

  1. 2
  2. 4 stars
    0
  3. 3 stars
    0
  4. 2 stars
    0
  5. 1 star
    0
Review this product
  • tonimel
    5
    2 out of 2 members found this review helpful

    Verified purchase

    I'm somewhere in the middle so far. Simple English, excellent balance of detail without too much blah blah. It says exactly what is needed. In almost every chapter, it starts with a description for understanding, and then goes straight to code and how it is applied – don't forget, it's hands on. There is math in several places, but in some parts there isn't and it focuses more on intuitive understanding. With how many things exist on the internet, this isn't an issue in my opinion. It's more of a hands-on book, if you want to go deeper there are countless free resources. Python knowledge is required, so if you don't know it, taking a Python course before starting the book will help a lot (e.g. CS50p).

    Translated from Greek ·
    Did you find this review helpful?
    • Paper quality
    • Was it easy to read?
    • Understanding of the subject matter
    • Was it interesting enough?
    • I liked the writing style
    • I would read a book by the same author
    • I would recommend it for reading
  • I'm somewhere in the middle so far. Simple English, excellent balance of detail without too much blah blah. It says exactly what is needed. In almost every chapter, it starts with a description for understanding, and then goes straight to code and how it is applied – don't forget, it's hands on. There is math in several places, but in some parts there isn't and it focuses more on intuitive understanding. With how many things exist on the internet, this isn't an issue in my opinion. It's more of a hands-on book, if you want to go deeper there are countless free resources. Python knowledge is required, so if you don't know it, taking a Python course before starting the book will help a lot (e.g. CS50p).

    Translated from Greek ·
    2
  • 0
  • See all
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