Responsible for approximately 1.35 million deaths each year, road-traffic accidents are currently the 8th leading cause of death globally.
In order for governments across the world to implement measures to reduce the number of fatalities caused by road traffic accidents, it is crucial to have as full an understanding of the main causes of these accidents and the circumstances under which they occur.
This purpose of this project is to perform an exploratory analysis of UK road accident data and to investigate the effectiveness of various machine learning tools and techniques in predicting the severity or other aspects of these accidents.
Multiple comprehensive datasets of road accidents occurring in the U.K. from 2005 to 2019 were collected, collated, and analysed, before being prepared for the machine learning models.
A variety of machine learning models were implemented and the predictive scores of these models were recorded.
Final year computing student on track for a 2:1 minimum.
3 years’ experience as a Business Analyst/ Insurance data analyst.
3 years’ experience in customer service in insurance domain. Strong skills in Java, Python, R, JavaScript - including NodeJS, ReactJS, MySQL, and DAX.
Strong interest in programming, algorithms and data structures, graph-theory, and also data-modelling, database design and backend development.