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Local Chapter project

Predicting RTC Severity using Machine Learning

Machine Learning
Start date
September 30, 2022
Finish date
October 31, 2022
Project status
completed
Predicting RTC Severity using Machine Learning

Challenge background

UK RTCs which have resulted in a persons death have been on a downward trend since the 1960s - however in 2020 1,516 people lost their lives on UK roads. The UK road systems, especially in Liverpool, are dated which means they have not been upgraded to reflect the increase of cars on the road. This means there are still preventative measures that could be implemented to prevent even more deaths on UK roads.

The UK government compiles and disseminates extensive data about road incidents around the nation (often once per year). This data is particularly fascinating and thorough for analysis and research because it contains, but is not limited to, geographic areas, weather conditions, vehicle types, casualty numbers, and vehicle manoeuvres.

Project timeline

  1. 1

    Week 1

    1. Data preprocessing

  2. 2

    Week 2

    2. Exploratory Data Analysis to draw insights

  3. 3

    Week 3

    3. Feature Engineering - creating new features based on insights drawn from EDA.

  4. 4

    Week 4

    4. Model Development

  5. 5

    Week 5

    5. Model Evaluation and Deployment - perhaps on AWS or Google Cloud.

What you'll learn

Data Processing, Exploratory Data Analysis, Feature Engineering, Model Development, Model Evaluation and Model Deployment.

Get involved

What to expect from a Local Chapter project

First project

  • Welcomes beginners and experienced practitioners.
  • Focuses on education and collaborative delivery.
  • Produces open-source project work.

Benefits

  • Address a significant real-world problem with your skills.
  • Build your project portfolio.
  • Demonstrate your work to organizations and project partners.

Requirements

  • Working English communication.
  • A learning mindset.
  • Commitment to collaborative project work.