Forward and backward propagation

1. What is forward and backward propagation?
2. What is forward and backward propagation in CNN?
3. What do you mean by forward propagation?
4. What does backward propagation do?

What is forward and backward propagation?

Backward Propagation is the process of moving from right (output layer) to left (input layer). Forward propagation is the way data moves from left (input layer) to right (output layer) in the neural network. A neural network can be understood by a collection of connected input/output nodes.

What is forward and backward propagation in CNN?

Forward Propagation is the way to move from the Input layer (left) to the Output layer (right) in the neural network. The process of moving from the right to left i.e backward from the Output to the Input layer is called the Backward Propagation.

What do you mean by forward propagation?

forward propagation means we are moving in only one direction, from input to the output, in a neural network. Think of it as moving across time, where we have no option but to forge ahead, and just hope our mistakes don't come back to haunt us.

What does backward propagation do?

Backpropagation, or backward propagation of errors, is an algorithm that is designed to test for errors working back from output nodes to input nodes. It is an important mathematical tool for improving the accuracy of predictions in data mining and machine learning.