Copyright
Brief Table of Contents
Table of Contents
Preface
Acknowledgments
About This Book
About the Author
About the Cover
1. Your machine-learning rig
Chapter 1. A machine-learning odyssey
1.1. Machine-learning fundamentals
1.1.1. Parameters
1.1.2. Learning and inference
1.2. Data representation and features
1.3. Distance metrics
1.4. Types of learning
1.4.1. Supervised learning
1.4.2. Unsupervised learning
1.4.3. Reinforcement learning
1.5. TensorFlow
1.6. Overview of future chapters
1.7. Summary
Chapter 2. TensorFlow essentials
2.1. Ensuring that TensorFlow works
2.2. Representing tensors
2.3. Creating operators
2.4. Executing operators with sessions
2.4.1. Understanding code as a graph
2.4.2. Setting session configurations
2.5. Writing code in Jupyter
2.6. Using variables
2.7. Saving and loading variables
2.8. Visualizing data using TensorBoard
2.8.1. Implementing a moving average