Demystifying second hand car market in Bangladesh using multimodal machine learning techniques

Abstract

When a person plans to buy or sell a car in an overly-crowded second-hand market, it is often difficult to estimate accurate prices. People are frequently duped by scalpers into purchasing cars that are not worth the base price. People even sell cars for far less or far more than the market valuation. We aim to establish a system that allows people to see a car's most recent anticipated value. Apparently, using multimodal supervised machine learning approaches, this study illustrates a second hand car price prediction system. Here, we will be using shallow machine-learning techniques and deep neural machine-learning techniques for such calculations. Then, the predictions will be compared and analyzed to find the precision of the best performance. We believe this research will provide us with the information we need to solve this challenge with high accuracy.