Inspiration
Basically, on halloween night, two days ago, we were looking for an uber and the prices were astronomically high
On the 31st, on Halloween night, our group decided to go to the party McGill was organizing. However, two of us did not get tickets in advanced, so unfortunately the group had to separate. While two of us were strolling around downtown, the two other ones got in the party. When the time came to order the Uber, the girls at the McGill party checked the prices at 1 am, and at their biggest surprise, it was 117$. This astronomically high price was our inspiration for our Hackathon project. We thought about the fact that many like us face the same problem each time they want to order an Uber, so we decided to build a website that could help all users predict the uber prices in a specific timeline.
What it does
This website is meant to help users see the predictions of uber prices so they can decide and lan ahead their rides. This website takes into account the destination, the location, the time of departure and the uber model desired (XL, Comfort, etc.)
How we built it
We decided to use a Uber dataset found online containing informations about pick-up, drop-offs, time frame, etc. Then, we coded a model on Google Collab that would train the model with the dataset and test it with some price prediction examples. After training and testing the model, we used Loveable to conceive our website model by prompting it with the features we wanted to included.
Challenges we ran into
A first, we had another project idea in mind, but unfortunately finding valuable datasets was too time consuming (to be further discussed during the presentation). Concerning our current project, our biggest challenge was to implement a Google Maps in our app and making sure it was predicting accurate prices according to our model.
Accomplishments that we're proud of
We are proud that we have a finished project at least. It is really far from perfection but we are proud that we learned new coding techniques. We are proud we made it this far and that we are confident enough on our presentation enough to present it in front of the judges.
What we learned
We learned new coding techniques, how to use our past knowledge at our advantage and how to be more efficient under a strict time line.
What's next for 2B2S
Built With
- google-maps
- googlecolab
- kaggle
- loveable
- python
- react
- typescript
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