Working of Back Propagation Network – Artificial Neural Network by Deeba Kannan
In this video, I explained the working of the Back Propagation Network in Artificial Neural Networks (ANNs), one of the most powerful techniques used to train deep learning models. Backpropagation helps in adjusting the weights of the network through error minimization, making it essential for neural network training.
Topics Covered:
Overview of the Back Propagation Network and its role in Artificial Neural Networks
Explanation of forward propagation in neural networks
How to calculate the error between the predicted output and actual output
Backpropagation process: Error propagation and weight updates
The significance of gradient descent in optimizing weights
Step-by-step working of Backpropagation Networks with an example
Importance of activation functions and learning rates in the process
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