Predicting-The-Costs-Of-Used-Cars---Hackathon-By-Imarticus-Learning | used car based on a given set

by sachink382 Python Version: Current License: No License

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Predicting-The-Costs-Of-Used-Cars---Hackathon-By-Imarticus-Learning is a Python library. Predicting-The-Costs-Of-Used-Cars---Hackathon-By-Imarticus-Learning has no bugs, it has no vulnerabilities and it has low support. However Predicting-The-Costs-Of-Used-Cars---Hackathon-By-Imarticus-Learning build file is not available. You can download it from GitHub.

Predict the price of a used car based on a given set of features discussed below. Size of training set: 6,019 records Size of test set: 1,234 records FEATURES: Name: The brand and model of the car. Location: The location in which the car is being sold or is available for purchase. Year: The year or edition of the model. Kilometers_Driven: The total kilometres driven in the car by the previous owner(s) in KM. Fuel_Type: The type of fuel used by the car. Transmission: The type of transmission used by the car. Owner_Type: Whether the ownership is Firsthand, Second hand or other. Mileage: The standard mileage offered by the car company in kmpl or km/kg Engine: The displacement volume of the engine in cc. Power: The maximum power of the engine in bhp. Seats: The number of seats in the car. New_Price: The price of a new car of the same model. Price: The price of the used car in INR Lakhs.

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