Foreword
Preface

Part I Building Models
1�� Introduction to TensorFlow
What Is Machine Learning?
Limitations of Traditional Programming
From Programming to Learning
What Is TensorFlow?
Using TensorFlow
Installing TensorFlow in Python
Using TensorFlow in PyCharm
Using TensorFlow in Google Colab
Getting Started with Machine Learning
Seeing What the Network Learned
Summary
2�� Introduction to Computer Vision
Recognizing Clothing Items
The Data�� Fashion MNIST
Neurons for Vision
Designing the Neural Network
The Complete Code
Training the Neural Network
Exploring the Model Output
Training for Longer-Discovering Overfitting
Stopping Training
Summary
3�� Going Beyond the Basics�� Detecting Features in Images
Convolutions
Pooling
Implementing Convolutional Neural Networks
Exploring the Convolutional Network
Building a CNN to Distinguish Between Horses and Humans
The Horses or Humans Dataset
The Keras Image Data Generator
CNN Architecture for Horses or Humans
Adding Validation to the Horses or Humans Dataset
Testing Horse or Human Images
Image Augmentation
Transfer Learning
Multiclass Classification
Dropout Regularization
Summary
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Part II Using Models

Index