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Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
Item #: 76232075

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

Item #: 76232075

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    Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.
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    What Stands Out

    Comprehensive Coverage
    This edition provides an extensive overview of both machine learning and deep learning, making it suitable for beginners and advanced users alike, ensuring a rounded understanding of Python frameworks.
    Hands-On Examples
    Includes practical examples using scikit-learn and TensorFlow 2, allowing readers to apply concepts directly in coding scenarios, enhancing learning and retention through real-world applications.
    Updated Content
    As a 3rd edition, it incorporates the latest advancements in machine learning and deep learning methodologies, ensuring readers are equipped with contemporary insights and techniques in the evolving tech landscape.

    Product Details

    Explore the power of Python for Machine Learning and Deep Learning with scikit-learn and TensorFlow. Discover the latest techniques in this 3rd edition book. Shop at Ubuy Saudi Arabia
    • Third edition of the bestselling Python machine learning book
    • Clear and intuitive explanations of machine learning techniques
    • Updated and expanded for TensorFlow 2, GANs, and reinforcement learning
    • Covers scikit-learn, TensorFlow, and PyTorch frameworks
    • Includes practical examples for image classification, sentiment analysis, and more
    • Suitable for beginners and intermediate readers
    Publisher Packt Publishing
    Publication date 12 Dec. 2019
    Edition 3rd Revised edition
    Language English
    Print length 770 pages
    ISBN-10 1789955750
    ISBN-13 978-1789955750
    Item weight 1.3 kg
    Dimensions 19.05 x 4.42 x 23.5 cm

    Who Should Buy?

    Suitable For
    • Aspiring Data Scientists

      Ideal for beginners looking to understand machine learning fundamentals and build a solid foundation in Python.

    • Software Developers

      Great for developers wanting to integrate machine learning capabilities into existing applications using Python libraries.

    • Students and Educators

      Suitable for academic purposes, providing clear explanations and practical examples for coursework or research.

    Not Suitable For
    • Complete Beginners

      Not suitable for those with no programming background, as some prior knowledge of Python is recommended.

    Product Description

    Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

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    AI & Machine Learning Editorial Review

    Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition is a comprehensive resource for both aspiring data scientists and those looking to deepen their understanding of machine learning. The book, published by Packt Publishing, spans 770 pages and offers extensive coverage of TensorFlow 2.0, making it ideal for readers with technical backgrounds in fields like computer science and mathematics. While many find it a valuable reference, beginners may encounter challenges with the required coding environment, which can complicate the learning experience. However, the structured approach to complex concepts is highly praised.

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    Pros

    • Extensive coverage of TensorFlow 2.0
    • Helpful for refreshing knowledge
    • Well-structured progression of topics
    • Excellent for junior data scientists
    • Technical details clearly explained

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