In the first chapter, you learned about the mathematics which drives the logic behind all kinds of neural networks. In this chapter, we are going to focus on the most fundamental neutral networks, which are called feedforward neural networks. We will also look at deep feedforward networks with multiple hidden layers to improve the accuracy of the model.
We will be covering the following topics:
- Defining feedforward networks
- Understanding backpropagation
- Implementing feedforward networks in TensorFlow
- Analyzing the Iris dataset
- Creating feedforward networks for image classification
