What is Gradient Descent and where is it used

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Accepted Answer

Gradient Descent is an optimization algorithm used to minimize the cost function of a machine learning model.

Gradient Descent is used in machine learning to find the optimal parameters of a model by minimizing the cost function
It works by iteratively adjusting the parameters in the direction of steepest descent of the cost function
There are two types of Gradient Descent: Batch Gradient Descent and Stochastic Gradient Descent
Batch Gradient Descent updates the parameters after computing the gradient of the cost function over the entire training set
Stochastic Gradient Descent updates the parameters after computing the gradient of the cost function over a single training example
Gradient Descent is used in various machine learning algorithms such as linear regression, logistic regression, and neural networks

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