Brick By Balance

Inspiration

In a real estate market where housing prices are rapidly increasing, home owners of the future may not have a clear financial plan on how to get onto the financial ladder. Brick By Balance aims to provide the future home owner with an idea of how housing prices will change as well as providing them with a strategy to reach this goal.

What it does

What it does The web app was built in Flask, with the back end being built in python, the model used was Prophet by FaceBook. How we built it

Challenges we ran into

The datasets available were either not large enough or did not contain the features that we wished to use in developing the model. We then had to perform extensive data pre processing on the chosen data set to maximise the productivity of the training.

Accomplishments that we're proud of

The team organisation was very effective in distributing the workload and playing to members' strength. We managed to rapidly develop two iterations of the ML model in a very short space of time. We delivered a sleek, functional website to allow user interaction

What we learned

How to integrate a ML model to a webpage,

What's next for Brick2Balance

Integrating banking APIs to seamlessly track user spending habits to help them achieve their goals =

Built With

• css
• flask
• html
• prophet
• python
• scikit-learn
• sql