  In this report, an automated bartender system was developed for making orders
in a bar using hand gestures. The gesture recognition of the system was
developed using Machine Learning techniques, where the model was trained to
classify gestures using collected data. The final model used in the system
reached an average accuracy of 95%. The system raised ethical concerns both in
terms of user interaction and having such a system in a real world scenario,
but it could initially work as a complement to a real bartender.
