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The project was implemented for a startup based in the US, who was building a mobile app for personalized restaurant menu recommendations.
Project Description:
As part of the project, we’ve scraped data about meals and menus from the internet. More than 7 million menu items from around 40,000 restaurants in the USA.
Feature extraction techniques were implemented in order to transform semi-structured data into a more useful representation. A personalized content-based menu recommendation system was created.
We’ve incorporated filtering techniques, specifically to deal with the cold start problem.
Technologies:
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