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 Ethiopia Local Chapter.

The problem

The levels of nitrogen, potassium, and phosphorus in the soil can become depleted over time, which can lead to reduced crop yields and poor plant growth. This depletion can occur due to factors such as over-farming, erosion, and environmental pollution. Additionally, variations in weather conditions can affect the availability of these minerals to plants, further complicating the harvesting process. This can make it difficult to maintain consistent crop yields and quality over time. As a result, it is important for farmers and agricultural researchers to monitor soil mineral levels. In this challenge, we will try to address a plant-type recommender system using the nitrogen, phosphorus, and potassium values of the soil. We will also consider the amount of temperature, humidity, and altitude in order to make our recommendations more accurate.

The goals

Our primary goal is to create a machine-learning model that can accurately recommend the type of plant we need to plant using the nitrogen, phosphorus, and potassium contents of the soil.

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