Machine learning beer tasting with Watson

The experience begins with a user being asked a series of colloquial questions about food preferences. Equipped with this information, Watson makes a recommendation of the three craft brews we think the taster will like best. Users then ranked the beers on a five-point scale, from favorite to least favorite.

The taster’s rankings are are automatically captured by the same object recognition technology, providing feedback to Watson to improve our recommendations over time.

For more information on the project, see the case study:

IBM Mobile Innovation Lab: