What is gradient descent in Machine learning?

Question

Can anyone explain gradient descent in Machine learning?

Answer 1

In Machine learning, gradient descent is an optimization algorithm used to find the parameters that minimize the cost function. Cost function represents the goodness of the model in predictions for those weights. In gradient descent, we start off randomly initializing values and slowly moves towards the steepest descent until the convergence point. We can adjust the size of steps by hyperparameter called the learning rate.

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Answer 2

Gradient descent is a mathematical technique especially used in neural networks to reduce the error in the training phase by figuring out how to modify the current values to get better results.

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