Abdul Kousa
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New York City Car Collision Prediction

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..