Gradient Descent for Machine Learning

Category: Education

It is an optimization algorithm to find the values of parameters(coefficient) of a function(f) that minimizes the cost function. It is used when parameters can not be calculated by Linear algebra. To minimize the cost function J(w) parameterized by a model parameter w. It tells about the slope of the cost function. To minimize the cost function we move in the direction of Gradient descent. It helps to scale the large dataset.