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  • TensorFlow for dummies
  • 點閱:27
  • 作者: by Matthew Scarpino
  • 出版社:John Wiley & Sons, Inc.
  • 出版年:2018
  • 集叢名:For dummies
  • ISBN:9781119466215
  • EISBN:9781119466192 ePub; 9781119466208 ePDF
  • 格式:EPUB 流式,PDF,JPG
  • 附註:Includes index. "Learning made easy"--Cover.

Become a machine learning pro!
 
Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy-to-follow book on the subject. Inside, you’ll find out how to write applications with TensorFlow, while also grasping the concepts underlying machine learning—all without ever losing your cool!
 
Machine learning has become ubiquitous in modern society, and its applications include language translation, robotics, handwriting analysis, financial prediction, and image recognition. TensorFlow is Google's preeminent toolset for machine learning, and this hands-on guide makes it easy to understand, even for those without a background in artificial intelligence.

 
Install TensorFlow on your computer
Learn the fundamentals of statistical regression and neural networks
Visualize the machine learning process with TensorBoard
Perform image recognition with convolutional neural networks (CNNs)
Analyze sequential data with recurrent neural networks (RNNs)
Execute TensorFlow on mobile devices and the Google Cloud Platform (GCP)
 
If you’re a manager or software developer looking to use TensorFlow for machine learning, this is the book you’ll want to have close by.


ABOUT THE AUTHOR

Matthew Scarpino has been a programmer and engineer for more than 20 years. He has worked extensively with machine learning applications, especially those involving financial analysis, cognitive modeling, and image recognition. Matthew is a Google Certified Data Engineer and blogs about TensorFlow at tfblog.com.

  • INTRODUCTION
    • About This Book
    • Foolish Assumptions
    • Icons Used in This Book
    • Beyond the Book
    • Where to Go from Here
  • PART 1: GETTING TO KNOW TENSORFLOW
    • CHAPTER 1: Introducing Machine Learning with TensorFlow
    • CHAPTER 2: Getting Your Feet Wet
    • CHAPTER 3: Creating Tensors and Operations
    • CHAPTER 4: Executing Graphs in Sessions
    • CHAPTER 5: Training
  • PART 2: IMPLEMENTING MACHINE LEARNING
    • CHAPTER 6: Analyzing Data with Statistical Regression
    • CHAPTER 7: Introducing Neural Networks and Deep Learning
    • CHAPTER 8: Classifying Images with Convolutional Neural Networks (CNNs)
    • CHAPTER 9: Analyzing Sequential Data with Recurrent Neural Networks (RNNs)
  • PART 3: SIMPLIFYING AND ACCELERATING TENSORFLOW
    • CHAPTER 10: Accessing Data with Datasets and Iterators
    • CHAPTER 11: Using Threads, Devices, and Clusters
    • CHAPTER 12: Developing Applications with Estimators
    • CHAPTER 13: Running Applications on the Google Cloud Platform (GCP)
  • PART 4: THE PART OF TENS
    • CHAPTER 14: The Ten Most Important Classes
    • CHAPTER 15: Ten Recommendations for Training Neural Networks
  • INDEX
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