Inspiration
What it does
We created a database for the buildings of montreal downtown area, containing information such as, address, coordinates, floors, units, height, etc, to be used for risk assessment estimations.
How we built it
scrapped the web pages containing useful information like real state websites and used Quebec open datasets on montreal assessments. Cleaned the data, estimated the missing values, and included all useful information.
Challenges we ran into
not structured data, incomplete data, insufficient data available.
Accomplishments that we're proud of
-- 3155 records -- 10 Attributes for each building -- Missing Data Prediction with AI -- User Friendly Interface to explore the dataset
What we learned
Using ML/AI in real scenario
What's next for WIMAIML
Hacking!
Built With
- datamining
- machine-learning
- python
- webapp
- webscraping
