I need an actual Python code, and please provide the result to see that it works. Thank you in advance !

You will be working on a housing dataset that is similar to the Boston Housing regression problem widely used in introductory machine learning classes. The documentation for this dataset may be found at: http://jse.amstat.org/v19n3 /decock/DataDocumentation.txt. The following code should get you started. import pandas as pd columns = ['Overall Qual', 'Overall Cond', 'Gr Liv Area', 'Central Air', 'Total Bsmt SF', 'SalePrice'] df = pd.read_csv('http://jse.amstat.org/v19n3/decock/AmesHousing.txt', sep =\t, usecols=columns) df.head() Compare the performance of the following models: Linear Regression, Lasso, Ridge, RandomForest. The metrics you will use to compare them are RMSE, MAE, and R-Squared. Your goal is to find a model that gives you the best performance