Chapter 2. Feed-Forward Neural Networks
In this chapter, we will implement Feed-Forward Neural Networks (FNN) and the building blocks for deep learning:
- Understanding the perceptron
- Implementing a single-layer neural network
- Building a multi-layer neural network
- Getting started with activation functions
- Hidden layers and hidden units
- Implementing an autoencoder
- Tuning the loss function
- Experimenting with different optimizers
- Improving generalization with regularization
- Adding dropout to prevent overfitting