Machine Learning applications to understand tendencies in Fatal Collisions

Closed
Toronto Police Service
Toronto, Ontario, Canada
Marissa Fosse
Senior Analyst
3
Preferred learners
  • Anywhere
  • Academic experience
Categories
Data analysis
Skills
machine learning artificial intelligence text mining predictive analytics
Project scope
What is the main goal for this project?

The Toronto Police Service (TPS) is undergoing continuous improvement efforts to enhance confidence and strengthen ties with our society by providing access to open data for public safety in Toronto.

The Service would like students to identify artificial intelligence and machine learning opportunities for the Fatal Collisions data* available on the Toronto Police Service’s Public Safety Data Portal (PSDP), in order to:

1) Derive insights and patterns, especially among potential relationships between variables, such as demographics, temporal data, impaired driving, DUI, and others

2) Build predictive analytics models

3) Create hot-spot mapping

4) Deliver a final report and/or presentation of findings and recommendations

*Consideration to be given on the use of text mining of street names and free form notes

Leveraging other open data sets, such as City of Toronto, weather-related data, or others to be identified by students, is recommended.

Fatal Collisions and other traffic related data can be found at http://data.torontopolice.on.ca/datasets/fatal-collisions

About the company

To Serve and Protect.

“We are dedicated to delivering police services, in partnership with our communities, to keep Toronto the best and safest place to be.”

Core Values:

- Service at our Core
- Do the right thing
- Connect with Compassion
- Reflect and Grow