Inspiration - As international students, it was really tough to find food that was close to the food that i was used to. Trying new food items which were not completely different from what i am used to.

What it does - It basically asks the user a few dishes that he likes and the deconstructs them based on ingredients, cuisine, spice level and a lot of other parameters and then suggests similar dishes with a closeness percentage.

How we built it - The Mobile App is built in react-native from scratch. The server is created in node JS and the backend database is in Posgress SQL.

Challenges we ran into - Getting the queries to run a matching algorithm to map the user entered dishes and map them to different columns in the database. Create a scoring algorithm to score various dishes on closeness and then show the top results.

Accomplishments that we're proud of - Built a clean and Appealing Mobile App from scratch. Learnt node from scratch, created a server and connect the Postgres database with it.

What we learned - New technologies like node, react and react-native and algorithms to optimize our search results

What's next for Food Guru- Implement a feedback-based system to improve the existing matching results. Save user preferences and use them next time along with the dishes he enters to suggest dishes more closely related to his taste.

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