RMSE
1- Ask the user to enter the: NAME (A, B, C, D, E, F, G, H, I, J), AGE, GPA (out of 4) and the MAJOR ( CS, CET, CIS, CE). Then print these information as follows: My name starts with the letter (NAME) and I am (AGE) years old. I study (MAJOR) and my GPA is: (GPA).
2- Repeat step 1 for 10 users with different values (Names can’t be repeated).
3- Store the entered information in the file students.CSV.
4- Plot the 4 features (NAME, AGE, GPA, and MAJOR) on separate figures using the seaborn library functions.
5- Define a function to evaluate the Root Mean Squared Error (RMSE) according to the following equation:
6- Calculate the mean() of the GPAs, and consider it to be the predicted value for all students () and consider the original GPA of the student to be
.
7- Compute the RMSE for each student according to the above equation (the squared root of the difference between the predicted and original GPA values). The value of m is 10 (number of the samples)
8- Store the computed RMSE values in the student.CSV file (as a new column entitled RMSE)
