Deep Learning Patterns and Practices

2 Deep neural networks

This chapter covers

• Breaking down the structure of neural networks and deep neural networks
• Using feed-forward and backward propagation during training to learn model weights
• Coding neural network models in both TF.Keras sequential and functional APIs
• Understanding the various types of model tasks
• Using strategies to prevent overfitting

This chapter starts with some basics on neural networks. Once you’ve gotten the basics down, I’ll introduce you to how deep neural networks (DNNs) can be easily coded using TF.Keras, which has two styles for coding neural networks: a sequential API and functional API. We will code examples using both styles.

This chapter also covers the fundamental types of models. Each model type, such ...