This mini-project will have you fitting a linear regression model to a dataset in order to predict Airbnb rental prices. After fitting a model, you will submit predictions on a subset of the original data that was removed. Whoever's predictions best fit the true prices will win!
The data
The data can be found in airbnb_berlin_listings.csv and contains data on Airbnb listings in Berlin.
The goal
Make predictions on the listing in the prediction_data.csv.
Deliverables
1) Use both gradient descent and OLS methods in building your linear regression model.
2) Submit a csv file containing the id and price of each of the listings in the prediction set.
Winner criteria
The winning model will have the lowest MSE on the prediction data.