From personal experiences, there are times when I want to eat out, but don't really have an idea of where exactly I want to eat. From there, my next plan of action would be to scroll through Yelp's list of restaurants to find a new place to dine. However, even though Yelp's services does offer an abundance of wonderful recommendations, at the end of the search, I always get overwhelmed with the number of options, and then find myself dinning at the same four restaurants that I always go. So, to prevent this, and encourage other users (and myself) to step out of my comfort zone and try out new restaurants, this app was created in a way that gave the users images of food and, from the users' preferences, output a recommend list of local restaurants to dine in.
What it does
This web application displays various images of cuisines to a user. After a set number of images displayed, the web application uses machine learning in order to "learn" which food dishes a user prefers. From there, the application returns a list of recommended restaurants suitable to the user.
How I built it
Challenges I ran into
Accomplishments that I'm proud of
We thought of a pretty cool idea that would be fun to use to help people decide what they may be interested in eating when they are not sure. It is not as complete as we would want it to be but it definitely was enjoyable to work on.
What I learned
We learned how to do web development better as well as the many useful API's that are available to us. We have become more comfortable with using the Yelp API as well as the AWS API calls.
What's next for Foodier