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Gradient Descent (i2tutorials)

Explain in detail about Gradient Descent?

Gradient descent is a first-order optimization algorithm. It is dependent on the first order derivative of a loss function. It calculates that which way the weights should be altered so that the function can reach a minima. Through back propagation, the loss is transferred from one layer to another and the model’s parameters also known as weights are modified depending on the losses so that the loss can be minimized.

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