Dynamic recommenders with Bayesian exploration are able to provide more accurate and personalized recommendations than traditional recommenders. By taking into account the user’s past behavior, the recommenders can adjust the recommendations to better fit the user.
Bayesian regression is a statistical method used to estimate the relationship between variables. It uses Bayesian inference, which is a form of statistical inference that relies on probability theory. In Bayesian regression, the relationships between variables are estimated through data rather than through assumptions.
During this session, participants will understand how to use our AI software to create a real-time recommender that delivers personalized recommendations to users based on their behavior and preferences.
