1. Consider the Student Performance dataset and do the following steps: a. Read carefully about the dataset which is provided for you. The explanation is available on the last page of this file. b. How does the quality of family relationships (famrel feature) affect the students grades? Plot G3 vs famrel for answering this question. After that, use simple linear regression for fitting the model and evaluate it by MSE and MAE metrics. c. Use multiple linear regression for finding the model according to students mother and father job and education (Mjob, Fjob, Medu, Fedu). Evaluate your model by using MSE and MAE metrics. d. Find a polynomial regression model using the absence feature. Use L1 and L2 regularization to find the optimum polynomial degree. e. Which features do you think are more important and have a greater impact on students scores? For answering this question, use the same evaluation metric for part b-d and compare the results. (Hint: Use pd.read_csv(data_name.csv, sep=; for reading the dataset)