Predicting the reason for their call

Inspiration

Montreal 311

What it does

Predicts with a 70% accuracy what the category of the call (the topic of conversation) is, given the date-time, weather, geographical location of the source call and the City of Montreal department receiving the call.

How I built it

Challenges I ran into

Unclean data Very unclean data A lot of data Less Compute Power. Google Colab wasn't a very great experience tbh.

Accomplishments that I'm proud of

Build a model that predicts decent!

What I learned

A lot about the AI space in Montreal, some of the exciting works some of the startups are doing and, in general, brushed up my ML which I hadn't touched in a while.

What's next for Predicting the reason for their call

1) Using calls data with crime data (use a reverse_geocoder to get the Arrondisments) 2) Using calls data with income data A lot of interesting things can be done with these 3.

Built With

• machine-learning