5. Neural Networks

• 5.1. Deep Learning
• 5.2. Neural Networks
• 5.3. RGB to Hue and Saturation
• 5.4. Information Flow: Making a Prediction
• 5.5. Calculating Errors
• 5.6. Training a Neural Network
• 5.7. Building a Neural Network for Regression
  • 5.7.1. Visualising Learning
• 5.8. Problem and Model Analysis
  • 5.8.1. 1. We need to train for longer
  • 5.8.2. 2. We need more training data
  • 5.8.3. 3. We need a larger neural network
  • 5.8.4. 4. The problem we are solving is hard
  • 5.8.5. 5. Selecting appropriate hyperparameters
• 5.9. Neural Networks for Classification
• 5.10. Building a Neural Network For Classification
• 5.11. More Advanced Neural Networks
  • 5.11.1. Dense Neural Network
  • 5.11.2. Convolution Neural Networks
  • 5.11.3. Recurrent Neural Networks
  • 5.11.4. Autoencoders
  • 5.11.5. Generative Adversarial Networks
  • 5.11.6. Transformers