3. Examples

• 3.1. Learning
• 3.2. Non-Linearly Separable
• 3.3. XOR Multiple Inputs/Targets
• 3.4. Activation Functions
• 3.5. Comparison
• 3.6. Datasets
• 3.7. Autoencoding
• 3.8. MNIST
• 3.9. EmbeddingLayer
• 3.10. LSTMLayer
• 3.11. Many to Many LSTM
• 3.12. Face Recognition
• 3.13. LSTM
• 3.14. CIFAR10 CNN
• 3.15. Working with Keras
• 3.16. Moving from Keras
• 3.17. Working with Camera and Networks
• 3.18. Plotting
• 3.19. Robot Simulation
• 3.20. Deep Dreams
• 3.21. Auto-encoder with Conv2D
• 3.22. Experiments
• 3.23. Making Movies
• 3.24. PCA
• 3.25. Under the Hood
• 3.26. Vision Quest
• 3.27. Teaching a Robot to Move
• 3.28. Network-Controlled Robot