Beginner's Guide to Deep Learning

We have already seen forward propagation while calculating the predicted value for the perceptron algorithm. 
## Feed forward in a neural network

Feedforward is the process that is used by neural networks to turn the given input into an output.

We have learned that the neural network is a combination of perceptrons. The perceptrons in each layer compute the output, apply the activation function, and passes that information to the next layer. This process continues until the output layer is reached. In short, each node feeds the information it has to the next node. That is why we call it a feed-forward propagation algorithm.

## Visualize feed-forward propagation
The following illustration shows a feed-forward propagation algorithm using a neural network with a hidden layer comprising of two hidden units below:

We have already seen forward propagation while calculating the predicted value for the perceptron algorithm. 
# Feed forward in a neural network

Feedforward is the process that is used by neural networks to turn the given input into an output.

We have learned that the neural network is a combination of perceptrons. The perceptrons in each layer compute the output, apply the activation function, and passes that information to the next layer. This process continues until the output layer is reached. In short, each node feeds the information it has to the next node. That is why we call it a feed-forward propagation algorithm.

# Visualize feed-forward propagation
The following illustration shows a feed-forward propagation algorithm using a neural network with a hidden layer comprising of two hidden units below:

Chapter 1

Feed forward Neural Network

Feed forward in a neural network