In these series of articles, we will provide you with a brief dictionary of terms surrounding data science including AI, machine learning, and deep learning.
Now, what is a Cost Function in Data Science?
In mathematical optimization and decision theory, a loss function or cost function is a function that maps an event or values of one or more variables onto a real number intuitively representing some “cost” associated with the event. An optimization problem seeks to minimize a loss function
A cost function represents a value to be minimized, like the sum of squared errors over a training set. Gradient descent is a method for finding the minimum of a function of multiple variables. So you can use gradient descent to minimize your cost function.