Understand the Linear Regression Technique
Linear regression combines a model and a technique for predictive analysis: the term 'linear' specifies that the model establishes a linear relationship between input parameters and output, while 'regression' refers to the technique used for making continuous predictions. Together, they form a supervised learning approach that uses the least squares method to fit the best line—or in higher dimensions, a hyperplane—to the data. This process can also be thought of as finding an approximate solution to an overconstrained system AX=B where an exact solution solving X given the constraints A and B doesn't exist. So under the hood, we find an approximate solution using linear 'fitting' or approximation techniques, which is what we call linear regression.