House Pricing Competition https://www.kaggle.com/c/house-prices-advanced-regression-techniques Step 1: train.csv and test.csv are the files which I have downloaded from Kaggle Community link provided above. Step 2: Data Preprocessing is done in kernel and code for it is provided in House_Pricing_Data_Cleaning.ipynb file. Step 3: After cleaning the data, the train and test files are saved as Final_Train.csv and Final_Test.csv Step 4: multiple_linear_regression.py and random_forest_regression.py contains the code for the respective algorithms. Step 5: The final submission files for both the algoritms are saved by adding their name at the suffix of file.