Gradient descent is a very important optimization technique that has been used by almost any neural network. In order to explain these techniques, I want to give an example. I have a dataset of students' scores and hours of study for each of the students. We want to predict the test scores of a student just by his amount of hours of study. You would say that this looks like an ML linear regression example. You are right; we are using linear regression to make a prediction. Why linear regression and what is the connection with gradient descent? Let me answer this and then we will see the code and some cool visualization.
Linear regression is the ML technique that uses statistical methods and allows us to study relationships ...
