In this video, we will understand forward propagation and backward propagation. Forward propagation and backward propagation in Neural Networks, is a technique we use in machine learning to train our Neural Network.
Forward propagation refers to propagating forward in our Neural network while calculating the values of Neurons in the Next layers.
While, we us Backward Propagation to train our weights W and bias B based on the given input dataset, to make accurate predictions.
After understanding, Forward propagation and backward propagation, you will be all set to implement Neural Networks in code.
Timestamps:
0:00 - Video Agenda
0:22 - Important Notations
1:52 - Matrix Represenation
2:45 - Forward Propagation in Action
4:06 - Random Weight Initialization
5:04 - Gradient Descent in Neural Network
7:21 - Backward Propagation in Neural Network
7:50 - Entire Process in Action
9:00 - Neural Network Equations
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