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

AUTHOR Gron Aurlien
PUBLISHER O'Reilly Media (10/15/2019)
PRODUCT TYPE Paperback (Paperback)

Description

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 Aur lien G ron 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
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Product Format
Product Details
ISBN-13: 9781492032649
ISBN-10: 1492032646
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
Edition Number: 0002
More Product Details
Page Count: 856
Carton Quantity: 12
Product Dimensions: 7.00 x 1.20 x 9.20 inches
Weight: 2.80 pound(s)
Feature Codes: Bibliography, Index, Price on Product, Illustrated
Country of Origin: US
Subject Information
BISAC Categories
Computers | Artificial Intelligence - Computer Vision & Pattern Recognit
Computers | Artificial Intelligence - Natural Language Processing
Computers | Data Science - Neural Networks
Dewey Decimal: 006.31
Descriptions, Reviews, Etc.
publisher marketing

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 Aur lien G ron 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
Show More
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Your Price  $51.74
Paperback