Android Description Example 1
Android Description Example 2
Android Lyft Service
iOS Home Page
iOS Description Example 3
iOS Description Example 1
iOS Description Example 2
There have been countless days when I have stepped into a car with my friends upon the realization that we had no idea as to what we wanted to do. Thus, my team and I came up with the idea of an app that would give a simple recommendation for a night out and learn from its users' preferences. We are all familiar with the examples of Tinder's swipe left/swipe right technique as well as with the concept of the like button. In Take Me Out, we strived to combine the simplicity of these features with machine learning tactics that would learn to give better and better recommendations to users.
What it does
Take Me Out presents the user with an option for a night out, simply a button click away. From user response through like and dislike buttons, the app collects data from the user and uses it to make more informed decisions from recommendation to recommendation
How we built it
We used the Yelp API to search for entertainment opportunities around our location as well as the Lyft API to get a ride there. We developed the app to be cross platform, with versions in both iOS Swift and Android Java.
Challenges we ran into
Our primary challenges were in properly integrating the API's that we wanted to use and in getting the machine learning techniques that we used to be responsive enough to be useful.
Accomplishments that we're proud of
We were able to develop the app for both iOS and Android, as well as use a variety of API's and other resources in order to get it done.
What we learned
It is incredibly helpful to strip an application down to what it's core components are and not to over embellish it with extraneous menus and settings. Having simple settings and API usage allow us to make the most of our user experience and machine learning tactics.
What's next for Take Me Out
We will most likely add some cloud integration (probably with Firebase) to allow user data to be stored on the cloud. We didn't do this here because of a desire for simplicity and immediate access, but use of cloud storage is probably the next step for this application.