Predicting Traffic Density in Istanbul Using Machine Learning

This Omdena Local Chapter Challenge runs for 5 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 Istanbul, Turkey Chapter.

The problem

The Turkish government has initiated several infrastructure projects and transportation improvements to alleviate the traffic density in Istanbul, however, the issue still remains a huge problem for the residents.

Predictive AI can provide valuable insights into traffic patterns and enable authorities to take proactive measures to reduce traffic density in Istanbul. It could optimize traffic flow in real-time, provide personalized travel recommendations, and ultimately lead to a more efficient and sustainable transportation system for the city.

The goals

• Develop a model that will predict traffic density levels accurately, using data from various sources, including IBB Data Portal, weather forecasts, event schedules etc. 
• Create an analysis to provide insight on factors affecting congestion, using data visualization tools.

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