TensorFlow Machine Learning Cookbook

Chapter 2. The TensorFlow Way

In this chapter, we will introduce the key components of how TensorFlow operates. Then we will tie it together to create a simple classifier and evaluate the outcomes. By the end of the chapter you should have learned about the following:

• Operations in a Computational Graph
• Layering Nested Operations
• Working with Multiple Layers
• Implementing Loss Functions
• Implementing Back Propagation
• Working with Batch and Stochastic Training
• Combining Everything Together
• Evaluating Models

Introduction

Now that we have introduced how TensorFlow creates tensors, uses variables and placeholders, we will introduce how to act on these objects in a computational graph. From this, we can set up a simple classifier and see how well it performs. ...