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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems Paperback – 31 Oct. 2022
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems Paperback – 31 Oct. 2022
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 Paperback – 31 Oct. 2022
Artigo n.º: 53210962

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems Paperback – 31

Artigo n.º: 53210962

AOA 70911

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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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O que se Destaca

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.

Detalhes do produto

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 Angola
Item Weight1.5 lbs (680 grams)

Quem Deverá Comprar?

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.

  • Casual Readers

    Individuals seeking light reading or non-technical content may find the technical details and hands-on approach overwhelming.

  • Non-Technical Users

    Users without a background in programming or data analysis will struggle to grasp the book's concepts and exercises.

DESCRIÇÃO DO PRODUTO

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems Paperback – 31 Oct. 2022

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Perguntas e Respostas dos Clientes

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

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

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

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

AI & Machine Learning Editorial Review

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AOA 70911

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Recursos e benefícios

  • Book explores machine learning techniques using Scikit-learn, Keras and TensorFlow
  • Suitable for programmers with no prior experience in deep learning
  • Covers a range of models from simple linear regression to deep neural networks
  • Includes code examples and exercises throughout the book
  • Dives into neural net architectures for computer vision, NLP, generative models, deep reinforcement learning
  • Explores unsupervised learning techniques like clustering, dimensionality reduction and anomaly detection

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