Predicting Fiber Uptake in an Area 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 Eldoret, Kenya Chapter.

The problem

Telco companies face a lack of data-driven and quantitative tools to assist in their fiber roll-out strategies, particularly in predicting household fiber uptake rates. Existing solutions primarily concentrate on cost calculations from providers like Comsof and Netadmin, rather than providing comprehensive support in identifying potential expansion areas.

Developing a tool that offers data-driven revenue predictions based on specific areas can significantly enhance the accuracy of expansion business cases. Gaining insights into the projected fiber uptake in households can serve as a valuable initial reference for decision-making.

The goals

• A model that can be able to predict the uptake rate of fiber.
• Visual map showing the most attractive fiber roll-out areas.

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