Following are the various steps we will walk together and try gaining an understanding. In this post, we will consider Linear Regression as the algorithm where the target variable'y' will be explained by 2 features'x1' and'x2' whose coefficients are β1 and β2. First up, lets get some minor prerequisites out of the way in order to understand their use down the line. Optional: Refer Chapter 3 in the link below to gain understanding about Linear Regression. In Fig 1(a) below, Gradient Descent is represented in 3-dim.