Car Accident Severity Analysis - Seattle Washington (Machine Learning Application)

An Apache-Spark application that infers qualitative data regarding the car accidents in New York City.

Capstone project for the Flatiron School's Immersive Data Science Bootcamp program. Uses time series modeling to predict car accidents in New York City, separated by borough.

Analysis of when and where New York City (NYC) vehicle collisions occur with a focus on collisions involving pedestrians and cyclists.

Data analysis of variables within car crashes in Pennsylvania's Allegheny county

Analysis of reported car accidents across the United States between 2016 and 2019. Python: Pandas, Matplotlib, and Plotly.

This project is our end project of data scientist certification with the continous formation LECEPE (https://www.lecepe.fr/certificats/data-scientist/).

Back end for a mobile app to allow citizens to report their own car accidents

Mobile app to allow citizens to report there own car accidents

Final Project for Higher Diploma in Data Analytics at National College of Ireland

Using geospatial data, this repository explores whether the location of popular clubs and bars in San Diego County is related to traffic collisions reported between 2015 and 2019.

Classifying Severity of US car accidents upon various attributes found in the Kaggle dataset titled, "US Accidents(3 million records)

Do men cause more car accidents than women?

A Data Visualization for Car Accidents in Utah

A Multiple Centrality Assestment of different US cities. The code included is part of the data analysis process of the thesis: "Decoding City Network: Exploring Urban Structure and Spatial Event Interplay Through Multiple Centrality Assessment"