- 01. Introducing Luis
- 02. Why "Neural Networks"?
- 03. Neural Network Architecture
- 04. Feedforward
- 05. Backpropagation
- 06. Training Optimization
- 07. Testing
- 08. Overfitting and Underfitting
- 09. Early Stopping
- 10. Regularization
- 11. Regularization 2
- 12. Dropout
- 13. Local Minima
- 14. Vanishing Gradient
- 15. Other Activation Functions
- 16. Batch vs Stochastic Gradient Descent
- 17. Learning Rate Decay
- 18. Random Restart
- 19. Momentum