Hands-On Machine Learning with Scikit-Learn and TensorFlow
Concepts, Tools, and Techniques for Building Intelligent Systems
Publisher: O'Reilly Media
Final Release Date: July 2016
Pages: 580

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A series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade. Now that machine learning is thriving, 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 how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.

This hands-on book shows you how to use:

  • Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry point
  • TensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networks
  • Practical code examples that you can apply without learning excessive machine learning theory or algorithm details
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5.0

Become Machine Learning God in one book

By Sylvain

from Paris

Verified Reviewer

Pros

  • Accurate
  • Concise
  • Easy to understand
  • Helpful examples
  • Well-written

Cons

    Best Uses

    • Expert
    • Intermediate
    • Novice
    • Student

    Comments about oreilly Hands-On Machine Learning with Scikit-Learn and TensorFlow:

    Hands On Machine Learning, that's exactly what it is. From chapter 2 on, you are given full power: it's not just theory, it is full-blown practice. The author is very comprehensive, must have been a teacher of some sort. Excellent in every possible way.

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    March 2017 (est.)