Overview:
In this master's Project, I delved into predicting dangerous car accidents in New York City achieving over 60% accuracy using traditional machine learning techniques. The project aimed to provide data-driven insights into the core reasons and contributing factors behind these accidents.
Data Sources:
The project Utilized multiple data sources: the NYC Motor Vehicle Collisions - Crashes dataset, Weather data, and Speed Limit data.
Tools and Technologies Used:
The project employed a range of techniques and models, including:
Key Highlights:
Learn More
For an in-depth and interactive exploration of this project, including methodologies, code, and more, please visit the project website here..