shelter-io
inspiration
In our society, one of the most fundamental problems data addresses is that of insight - not only into the world we live in, but how we choose to live in it. In our modest attempt to address these problems, we leveraged the power of machine learning, the security of the blockchain, and the complex structures that mapping data helped us leverage. In doing so, we've created the perfect tool for home planners, real estate investors, construction companies, and companies alike.
what it does
shelter.io provides a next-generation interface to provide real time interaction and exploration of complex financial indicators and derivatives and their correlation to local and global real estate markets. With deep connections to the underlying assets powering these markets, we believe that these insights will power the future decisions made by everyone.
how we built it
shelter.io runs on magic, fairy dust, a collection of python 3 libraries, the quandl datsets, and an unstoppable drive to change the world.
challenges we ran into
After generating relevant correlation and sensitivity data through aws, we were unable to properly bind our data to the visualizations created by the mapping software.
Required Libraries:
- Pandas
- Folium
- Quandl
Built With
- jupyter-notebook
- python
Log in or sign up for Devpost to join the conversation.