Using a prehistoric dataset of around 6000 cars for training our Machine Learning model. After training, the model which gave an accuracy of 87% was pickled and embedded in the Django web application. The web app asks for the features of the car you want to sell like make, model, engine size, fuel, seating cap, miles driven, number of owners, etc and applies this data to the ML model to give the predicted price of the car to ensure the buyer that he is paying the acceptable price for that used car.

Government pours in a gigantic sum of money for Waste management in our country, but still, people find it difficult to do a small bit on their side, which is to segregate the biodegradable and non-biodegradable waste. In this regard, I designed a Sensible bin that applies image recognition using Machine Learning to classify the waste into the 2 stated types.