Autorola, who specializes in online car remarketing, has car auctions running daily and many customers are bidding throughout a day. The valuable auction data such as car information and customer information are available in Autorola’s database, however the data is raw and not analyzed or processed to obtain higher-level information using Machine Learning. We wish to develop a system in collaboration with Autorola, where we use their raw auction data to create Machine Learning models to predict customers’ bid behaviour.
Aims and Objectives
This project aims to train, validate and test models to predict Autorola’s customer bid behaviour, as well as integrating those models into an interface that Autorola can use for future predictions. Those models will help Autorola to understand and predict the customer’s behaviour in an auction. To achieve accurate predictions, acknowledged Machine Learning techniques will be used.
How can we predict Autorola’s auction customers’ behaviour by using historical data and Machine Learning techniques?