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This video on Backpropagation in Neural Networks will cover how backpropagation and gradient descent play a role in training neural networks. You will learn this using an example of how to recognize handwritten digits using a neural network. After predicting the results, you will see how to train the network using backpropagation to obtain high-accuracy results. You will also understand how to calculate the loss function to measure the error in the model. Finally, you will look at how to find the minimum of a function using gradient descent with a graph's help.

00:00 - Introduction to Neural Network

00:18 - Working of Neural Network

02:07 - Real time example to build a Neural Network

04:23 -Calculation of Loss function

05:18 - Gradient descent in Neural Network

07:00 - What is Backpropagation?

07:08 - Working of Backpropagation

08:20 - Backpropagation in Gradient descent

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