Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
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.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
Nr produktu: 53210962

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

Nr produktu: 53210962

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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.
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Co wyróżnia ten produkt

Comprehensive Coverage
This book offers an in-depth exploration of essential machine learning concepts, tools, and techniques, making it suitable for beginners and experienced practitioners alike looking to build intelligent systems.
Hands-On Approach
With practical examples and exercises, readers gain hands-on experience in applying Scikit-Learn, Keras, and TensorFlow, ensuring they can effectively implement machine learning projects in real-world scenarios.
Up-to-Date Content
Published in November 2022, this book incorporates the latest advancements in machine learning, providing readers with current strategies and practices that reflect today's rapidly evolving technology landscape.

Szczegóły Produktu

Get your hands on the latest edition of the bestselling book to learn concepts, tools, and techniques to build intelligent systems. Paperback available - 31 Oct. 2022. Shop at Ubuy Polska
  • 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
Publisher O'Reilly Media
Publication date 31 Oct. 2022
Edition 3rd
Language English
Print length 861 pages
ISBN-10 1098125975
ISBN-13 978-1098125974
Item weight 1.36 kg
Dimensions 18.42 x 5.08 x 24.13 cm

Dla kogo jest przeznaczony?

Suitable For
  • Beginner Learners

    Newcomers to machine learning who want a comprehensive introduction with practical examples and clear explanations will benefit greatly.

  • Data Scientists

    Professionals looking to enhance their practical skills in building machine learning models using popular libraries like TensorFlow and Keras.

  • Computer Science Students

    University students studying machine learning concepts who need a resourceful guide with hands-on coding exercises and projects.

Not Suitable For
  • Advanced Practitioners

    Experienced data scientists may find the content too basic and lacking in depth for their advanced needs.

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Pytania i odpowiedzi klientów

  • pytanie: What programming language is used in this book?

    odpowiedź: The book uses Python programming language with Scikit-learn, Keras, and TensorFlow frameworks.
  • pytanie: Do I need prior experience in deep learning?

    odpowiedź: No, the book is suitable for programmers with little to no prior experience in deep learning.
  • pytanie: Does the book cover unsupervised learning techniques?

    odpowiedź: Yes, the book covers unsupervised learning techniques such as clustering, dimensionality reduction, and anomaly detection.

AI & Machine Learning Editorial Review

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The "Hands–On Machine Learning with Scikit–Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems" book has received a mixture of positive and negative feedback. The majority of the reviews praise the book for its comprehensive and practical approach to machine learning and AI. Customers appreciate the practical examples and the high density of information, with one reviewer even calling it a masterpiece. The book is described as a substantial and invaluable resource for anyone working on machine learning projects. Clear explanations and working code examples are also highlighted as key positives. However, there are also complaints about the packaging and protection of the book during delivery, as well as the overwhelming amount of content, which some found challenging to retain. A potential need for supplementary resources or further reading is also mentioned.

Opinie i oceny klientów

877 oceny klientów
  • 5 gwiazdka
    83%
  • 4 gwiazdka
    10%
  • 3 gwiazdka
    3%
  • 2 gwiazdka
    1%
  • 1 gwiazdka
    3%

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Podziel się opinią z innymi klientami

Zalety

  • Comprehensive and practical approach to machine learning and AI
  • High density of information
  • Substantial and invaluable resource for machine learning projects
  • Clear explanations and working code examples

Wady

  • Overwhelming amount of content

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