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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
Vara #: 53210962

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

Vara #: 53210962

ISK 15976

ISK 21759

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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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What Stands Out

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.

Upplýsingar um vöru

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 Iceland
  • Book designed for readers with Python programming experience and familiarity with main scientific libraries
  • Suitable for those interested in machine learning applications such as customer segmentation, product recommendation, fraud detection, and revenue forecasting
  • Intended to provide concepts, tools, and intuition needed to implement programs capable of learning from data
  • Covers a wide range of techniques, from simple to deep learning algorithms, utilizing production-ready Python frameworks like Scikit-Learn, TensorFlow, and Keras
  • Scikit-Learn is user-friendly and implements many machine learning algorithms efficiently, making it a great entry point to learning machine learning
  • TensorFlow and Keras offer more complex and high-level deep learning capabilities, with TensorFlow supporting large-scale machine learning applications
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

Who Should Buy?

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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Spurningar og svör viðskiptavina

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

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

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

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

AI & Machine Learning Editorial Review

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