Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques for Building Intelligent Systems

Aurélien Géron

  • 出版商: O'Reilly Media
  • 出版日期: 2017-04-09
  • 售價: $1,685
  • 貴賓價: 9.5$1,601
  • 語言: 英文
  • 頁數: 572
  • 裝訂: Paperback
  • ISBN: 1491962291
  • ISBN-13: 9781491962299
  • 相關分類: Machine Learning 機器學習DeepLearning 深度學習TensorFlow
  • 銷售排行: 🥉 2018/7 英文書 銷售排行 第 3 名
    👍 2017 年度 英文書 銷售排行 第 11 名
    🥉 2017/7 英文書 銷售排行 第 3 名
    🥈 2017/5 英文書 銷售排行 第 2 名

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Through a series of recent 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 practical book shows you how.

By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.

  • Explore the machine learning landscape, particularly neural nets
  • Use scikit-learn to track an example machine-learning project end-to-end
  • Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
  • Use the TensorFlow library to build and train neural nets
  • Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
  • Learn techniques for training and scaling deep neural nets
  • Apply practical code examples without acquiring excessive machine learning theory or algorithm details