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
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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
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
物品 #: 278397950

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

物品 #: 278397950

HKD 797

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What Stands Out

Comprehensive Coverage
This book offers an in-depth exploration of machine learning concepts, tools, and techniques, providing readers with a well-rounded understanding needed to build intelligent systems effectively.
Hands-On Approach
Filled with practical examples and hands-on projects, this resource engages learners actively, enabling them to apply theoretical knowledge to real-world machine learning challenges.
Updated Content
The third edition includes the latest advancements in Scikit-Learn, Keras, and TensorFlow, ensuring readers are well-versed with current practices and technologies in the rapidly evolving field of machine learning.

產品詳情

Shop Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems online at a best price in 香港. 1098125975
  • 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 1 Nov. 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

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Hands-On Machine Learning with Scikit-Learn Keras and TensorFlow 3e: Concepts Tools and Techniques to Build Intelligent Systems is an invaluable resource for anyone delving into the world of machine learning. This comprehensive guide, spanning 861 pages, effectively covers essential concepts and hands-on examples that enhance understanding, making it ideal for beginners and experienced users alike. Readers have praised its structured approach and the breadth of algorithms provided for various machine learning problems. However, it is advisable to have a foundational knowledge of Python and statistics to maximize the benefits from the content. Additionally, while the printed version may have difficulty staying open during coding exercises, alternatives exist for those who prefer digital formats.

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優點

  • Comprehensive coverage of machine learning concepts
  • Hands-on examples throughout the book
  • Well-structured and easy to follow
  • In-depth explanation of various algorithms
  • Ideal for both beginners and advanced learners

缺點

  • Printed version may close while writing code

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