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DATA

Data is webscraped from sahibinden.com. The column names are brand name, model, KM, model year, engine type and fuel type.There are 63 unique car brands in my data.

MODELS USED

I have used multiple linear regression, decision tree regressor and random forest regressor. 
I compared their R2 scores and MSE in order to evaluate which model is best.

FILES

Prediction of Used Car Prices.ipynb Interactive Python Notebook that includes the code itself
sahibindenscraper.py The code in order to get data from sahibinden.com