Authors

Inspiration

ML integrated app and online forums that recommend things to users every day.

What it does

It recommends restaurants accroding to users' locations, cuisine preferences and our algorithm to recommend new restaurants.

How we built it

  • Build multiple types of machine learning models that recommend restaurants.
  • Utilize firebase database.
  • Deploys on our server.
  • Create front-end user interface.

Challenges we ran into

It is hard to buiild communication protocols between machine learning models and server and between server and front-end.

Accomplishments that I'm proud of

Successfully build an ML integrated App that supports restaurant recommendations, recommendation updates, social grouping and chatting.

What we learned

Much about recommendation algorithm, much on industrial level database organization.

What's next for Go Eat

Improve our ML algorithms, make the firebase database more organized.

Try It out

Hackathons

Technologies

django, firebase, flutter, jupyter-notebook

Devpost Software Identifier

256045