In this blog, we are going to discuss the most important algorithm in machine learning and deep learning Linear Regression. "In Linear Regression Our Main Task is to find the best fitted line" As we see on the plot above that the best-fitted line on the data points is L0. There can be more best-fitted lines on the data points like l1, and l2, etc. then the question is, how do we find the best-fitted line above all of them?? We calculate the distance of the line from each point in the graph then find the MSE. After that, whichever line gives us the minimum error, we choose that line as our best-fitted line. In the plot below, we are measuring the distance of L0 From all the points and then just finding the error and comparing it with other lines.