Locked in

Inspiration

using features from popular applications such as Tinder and Instagram then combining it with proven study habits to create the optimal resource in uniquely solving student's day-to-day struggles with time problems.

What it does

Lets users look for study groups to increase accountability of students. A machine learning algorithm will assist by providing more weighting to a specific attribute depending on what users find to be most popular. IE: if everyone filters by discipline, it will add weighting to the discipline attribute generating smarter matches for users.

How we built it

Website was developed using NodeJS, React and Flask frameworks facilitated by JavaScript, HTML, CSS, and Python to create an interactive website. Furthermore, the utilization of Python allowed for a streamline approach to implementing a Machine Learning algorithm - our proudest feature.

Challenges we ran into

We found the biggest problem was collaborating with one-another using GitHub as certain conflicts required time - our biggest constraint. We believe had time not been an issue, we would have overcome and been capable of fully implementing a much more developed application

Accomplishments that we're proud of

We managed to implement an algorithm that was fully functional according to our requirements. Furthermore, the website we created satisfied our design requirement.

What we learned

We learned project management techniques such as deadlining, allocating tasks and providing feedback using code reviews and testing. Using github branches was also a new concept for us and navigating merge branches in a production situation like rather than purely academic.