Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
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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
Nº de artículo: 53210962

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

Nº de artículo: 53210962

MXN 1867

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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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Lo que 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.

Detalles de producto

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 Mexico
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

¿Quién Debería Comprarlo?

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.

DESCRIPCIÓN DEL PRODUCTO

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

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Preguntas y respuestas de los clientes

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

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

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

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

AI & Machine Learning Editorial Review

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.

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Ventajas

  • 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

Desventajas

  • Overwhelming amount of content

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MXN 1867

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Características y beneficios

  • 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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