Q: What is a linear regression? A: It is all about getting the best fit line that supports linearity. The relation between independent and dependent variables helps to form a Straight Line. Q: Assumptions of Linear regression? A: a)The relation between independent and dependent variables that supports Linearity. b)Multicollinearity.The relation between one feature with other feature c) Homoscedasticity: It means the same distribution of error for all the independent variables. d) Hetrosedasticity: it is quite opposite to Homescedasticity.no Equal distribution of the errors . Q: Regression problems evaluation metrics and which one we have to use? A: In regression problems, we are having a different type of evaluation metrics like RMSE, MSE, MAE, etc. And now the question is which one we have to use? for regression problems, we can use any metrics to calculate the score but in Compilation time we use MAE(mean absolute error), which save...