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The project originally came up after discussing with my friends how fun it is to hack for new places in the city, finding new spots, bars, restaurants that just fit my style and taste. Nowadays, most platforms suits place to users by ranking them, without taking into consideration information that implies what kind of atmosphere a restaurant has…

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Flavorite

The project originally came up after discussing with my friends how fun it is to hack for new places in the city, finding new spots, bars, restaurants that just fit my style and taste. Nowadays, most platforms suits place to users by ranking them, without taking into consideration information that implies what kind of atmosphere a restaurant has. Using collaborative Filtering, I tried to build a platform that will offer users recommendations for new restaurants based on their favorite places. The platform compares the user’s preferences to users that share the same preferences and offers him the places which he does not know and suits him the best.

DEMO: https://drive.google.com/file/d/1YjGQG8ODZfs3-XzIQhjKqGFYjZgaXcsv/view

Course: AI and ML for interactive products

Guiding: Michael Fink

Special thanks to Gilad Schreiber for the web template

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The project originally came up after discussing with my friends how fun it is to hack for new places in the city, finding new spots, bars, restaurants that just fit my style and taste. Nowadays, most platforms suits place to users by ranking them, without taking into consideration information that implies what kind of atmosphere a restaurant has…

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