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Table Of Contents
1 Introduction
2 What Is Deep Learning?
3 Image Fundamentals
4 Image Classification Basics
5 Datasets for Image Classification
6 Configuring Your Development Environment
7 Your First Image Classifier
8 Parameterized Learning
9 Optimization Methods and Regularization
10 Neural Network Fundamentals
11 Convolutional Neural Networks
12 Training Your First CNN
13 Saving and Loading Your Models
14 LeNet: Recognizing Handwritten Digits
15 MiniVGGNet: Going Deeper with CNNs
16 Learning Rate Schedulers
17 Spotting Underfitting and Overfitting
18 Checkpointing Models
19 Visualizing Network Architectures
20 Out-of-the-box CNNs for Classification
21 Case Study: Breaking Captchas with a CNN
22 Case Study: Smile Detection
23 Your Next Steps
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