Edited code examples from the book 'Deep Learning for Computer Vision - Starter Bundle' by Adrian Rosebrock.

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