2.Compute –Do the same as above but now with Time on App and Yearly Amount Spent. Is this correlation stronger than 1stOne?
3.Compute –Explore types of relationships across the entire data set using pairplot . Based off this plot what looks to be the most correlated feature with Yearly Amount Spent?
4.Compute –Create linear model plot of Length of Membership and Yearly Amount Spent. Does the data fits well in linear plot?
5.Compute –Train and Test the data and answer multiple questions –What is the use of random_state=85?
6.Compute –Predict the data and do a scatter plot. Check if actual and predicted data match?7.What is the value of Root Mean Squared Error?
Answer to : Question 139675