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ML Based Old Car Price Prediction Based On Multiple Features Like Mileage, Brand, Model, Fuel Type Etc.
The automotive industry is composed of a few top global multinational players and several retailers. The multinational players are mainly manufacturers by trade whereas the retail market features players who deal in both new and used vehicles. The used car market has demonstrated a significant growth in value contributing the larger share of the overall market. The used car market in India accounts for nearly 3.4 million vehicles per year.
To build a supervised machine learning model for forecasting value of a vehicle based on multiple attributes.
Since this is a classification problem, we have implemented two algorithms – K Nearest Neighbor (KNN), Multiple Linear Regression, Gradient Boosting and Decision tree Regression and compared the two on different models of vehicles. All this is done in python using scikit-learn ML library .
List of Deliverables
2. Python codes