TensorFlow Machine Learning Cookbook

Amazon.com Price: $54.99 (as of 05/05/2019 14:19 PST- Details)

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Description

Key Features

  • Your quick guide to implementing TensorFlow in your day by day machine learning activities
  • Learn advanced techniques that bring more accuracy and speed to machine learning
  • Upgrade your knowledge to the second one generation of machine learning with this guide on TensorFlow

Book Description

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will help you dig deeper and gain more insights into your data than ever before. You can work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning each and every the usage of Google’s machine learning library TensorFlow.

This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and more than a few data sources. Moving ahead, you’ll get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.

Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.

What you’ll learn

  • Become familiar with the basics of the TensorFlow machine learning library
  • Get to know Linear Regression techniques with TensorFlow
  • Learn SVMs with hands-on recipes
  • Implement neural networks and reinforce predictions
  • Apply NLP and sentiment analysis to your data
  • Master CNN and RNN through practical recipes
  • Take TensorFlow into production

About the Author

Nick McClure is currently a senior data scientist at PayScale, Inc. in Seattle, WA. Prior to this, he has worked at Zillow and Caesar’s Entertainment. He got his degrees in Applied Mathematics from The University of Montana and the College of Saint Benedict and Saint John’s University.

He has a passion for learning and advocating for analytics, machine learning, and artificial intelligence. Nick on occasion puts his thoughts and musings on his Twitter account, @nfmcclure.

Table of Contents

  1. Getting Started with TensorFlow
  2. The TensorFlow Way
  3. Linear Regression
  4. Support Vector Machines
  5. Nearest Neighbor Methods
  6. Neural Networks
  7. Natural Language Processing
  8. Convolutional Neural Networks
  9. Recurrent Neural Networks
  10. Taking TensorFlow to Production
  11. More with TensorFlow

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