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Computer Vision with Python 3 by Saurabh Kapur

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Training a network

Once we have the network design in place, we can now start training the network. The training phase of any neural network comprises two parts: first, feed forward the input and second, backpropagate the error. Let's understand each of them separately.

Feed forward means to take the input and pass it through the perceptrons in our network and calculate the output using the perceptrons. The input values are multiplied with the weights values of the perceptrons and an output is generated.

While backpropagating, we take the feed forward output (from the last step) and find its difference from the actual output (ground truth). Using this error, we modify the weights of the perceptron. You can think of the weights of each perceptron ...

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