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TensorFlow Machine Learning Cookbook by Nick McClure

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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. ...

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