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Mitigating Misdemeanors with Maps and Models
With the Montreal Crime dataset and hockey data, we found some correlations between win rates and crime. Are you ready to uncover an unexpected connection between sports and crime?
Exploring Montreal Crime Dataset and running machine learning models on it
We analyzed Montreal crime data and created interactive visualizations to deliver data-driven insights for policy makers.
Fighting crime rates in Montreal by promoting a sense of community.
Goofy Ahh Scientists present Montreal Crime Analysis: A study and proposed policy changes to improve the quality of life.
Does sepsis target people based on their race or ethnicity? How does treatment in these individuals compare? Find out in under five minutes.
Creating a search function to input an address and match it an existing one.
Using Python along libraries such as pandas, matplotlib and scikit, we analyze Montreal crime data in order predict the relative likelihood of each crime type to occur in a given area.
This project analyzes the large MIMIC-III Dataset and showcases the trends and patterns that exist concerning an individual's likelihood to encounter sepsis.
We analyzed trends across many time and location metrics to find the most dangerous time, place, and time of year in Montreal and judged significance with logistic regression.
An analysis of the Montreal Crime Data set. Contains some data visualization and a trained ML classifier.
Analyzing clinical data and make predictions about patients with Sepsis.
We looked at the rates of breaking and entering and provided insight on possible solutions to mitigate this action.
Staying safe in Montreal: know the most likely crime to occur based on time and location (police district of Quebec)
Web app for Spotify song recommendations based on facial emotions detection.
Montreal Crime Monitor: Patterns, Trends, and Solutions
We analyze crime statistics and data
Analyze the sepsis rate with different features (gender, race, common other diseases).
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