Linear Regression using Scikit-learn and Tensorflow.

Linear Regression is a supervised machine learning algorithm that is used to model a linear relationship between the dependent and independent variables. In other words, it best fits the linear line between the independent and dependent variables. A Linear Regression model main aims to find the best fit linear line and minimize the error by finding the optimal values of intercept and coefficient. Error is the difference between the actual value and the predicted value. Error is the difference between the actual value and the predicted value.