Analyzing Air Quality in Gurugram Using Machine Learning

This Omdena Local Chapter Challenge runs for 4 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by Omdena Gurugram, India Chapter.

The problem

Machine learning-based analysis of air quality data can provide valuable insights into the patterns, trends, and underlying factors contributing to air pollution in Gurugram. By leveraging machine learning algorithms, it is possible to develop predictive models, identify sources of pollution, and assess the effectiveness of control measures. This information can then be used to inform policy decisions and develop targeted interventions to reduce air pollution in Gurugram and other cities in India and create awareness among the general public about the severity of air pollution in the city and its effects on their health and well-being. 

The goals

The goals of this project are: 

• Identifying possible data sources
• Relevant Data Collection
• Data Cleaning and Preprocessing
• Developing AQI calculation strategy
• Evaluating trends and patterns in AQI and other parameters
• Applying machine learning modeling
• Model training and evaluation
• Deploying model as an API using FastAPI

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work