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TensorFlow For Machine Intelligence
"Finally a TensorFlow book for humans." – Guillaume Binet, Creator of Errbot
A hands-on introduction to learning algorithms
TensorFlow, a popular library for machine learning, embraces the innovation and community-engagement of open source, but has the support, guidance, and stability of a large corporation. Because of its multitude of strengths, TensorFlow is appropriate for individuals and businesses ranging from startups to companies as large as, well, Google.
TensorFlow is currently being used for natural language processing, artificial intelligence, computer vision, and predictive analytics. TensorFlow, open sourced to the public by Google in November 2015, was made to be flexible, efficient, extensible, and portable. Computers of any shape and size can run it, from smartphones all the way up to huge computing clusters.
Part I. Getting Started with TensorFlow
- CHAPTER 1: Introduction
- CHAPTER 2: TensorFlow Installation
Part II. TensorFlow and Machine Learning Fundamentals
- CHAPTER 3: TensorFlow Fundamentals
- CHAPTER 4: Machine Learning Basics
Part III. Implementing Advanced Deep Models in TensorFlow
- CHAPTER 5: Object Recognition and Classification
- CHAPTER 6: Recurrent Neural Networks and Natural Language Processing
Part IV. Additional Tips, Techniques, and Features
- CHAPTER 7: Deploying models in production
- CHAPTER 8: Helper Functions, Code Structure, and Classes
- CHAPTER 9: Conclusion