Data-Science Numerical Methods Project Solution

Project Description
Rusty Bargain used car sales service is developing an app to attract new customers. In that app, you can quickly find out the market value of your car. You have access to historical data: technical specifications, trim versions, and prices. You need to build the model to determine the value.
Rusty Bargain is interested in:
the quality of the prediction; the speed of the prediction; the time required for training
Project instructions
1) Download and look at the data. 2) Train different models with various hyperparameters. Compare gradient boosting methods with random forest, decision tree, and linear regression. 3) Analyze the speed and quality of the models.
Data description
The dataset is stored in file /datasets/car_data.csv. download dataset.
Features
VehicleType — vehicle body type
RegistrationYear — vehicle registration year
Gearbox — gearbox type
Power — power (hp)
Model — vehicle model
RegistrationMonth — vehicle registration month
FuelType — fuel type
Brand — vehicle brand
NotRepaired — vehicle repaired or not
NumberOfPictures — number of vehicle pictures
Target
Price — price (Euro)