AI for Good: When Your Laptop and Coffee Mug Start Impacting Lives
Omdena has proven to be a confidence-boosting tablet for me.
Working for multinational corporations (MNCs) and collaborating with global teammates is still a dream for many professionals like me. Omdena provides a prominent platform for working globally and collaborating with peoples from all around the world with diverse backgrounds.
After completing certifications from Stanford University, my interest in AI reached the zenith. I worked on projects provided by open platforms like Kaggle and Github. Though it was not really enjoyable. I was way more interested in working on real-world projects.
On Linkedin, I came across Omdena. I visited the website and applied with nervousness. Luckily, I cracked the interview and got a selection email within two weeks. I was so excited about this project because I was going to collaborate with 50 people from more than 20 countries. I was selected for the project “Impact assessment of Desert Locust in Kenya”.
The project: Minimizing the spread of desert locust
Kick-off Meeting: At our very first meeting we were informed about the working methodologies of Omdena along with our responsibilities. We came from different backgrounds and various time zones. Initially, things were looking unorganized but steadily the creative chaos turned into a meaningful and clear picturesque.
Task Manager: Omdena not only allowed me to recognize my skill sets but also pushed me to go beyond my comfort zone. The work was divided into tasks and the Task Manager role was given. Before the meeting, I decided to contribute technically, but in the meeting, I accepted the position of task manager with fear. Our Project Manager assigned me the role to boost my confidence. It allowed me to nurture my leadership skills, project management, and working experience. Within a short time, seniors from Omdena appreciated my work as a Task Manager. The support shown by seniors and team members is always going to remain in my heart!
Working with satellite imagery and building a vegetation classifier
The project had two aims. First, building a vegetation classifier, and second, developing an impact assessment analysis of a desert locust attack in Kenya.
According to FAO, damage caused by desert locusts is expected to destroy 40 percent of pastureland and leads to harvest losses of up to 25 percent. This would cause an additional 5.5–11 million people to face severe acute food insecurity, malnutrition, and hunger.
We worked on satellite imagery data from Eurosat and Sentinental-2. Omdena allowed us to work with our ideas so we used many approaches to get the highest performance score. We worked so hard until the end of the project and each one was contributing at their own pace in their way. This was the most beautiful and enjoyable working methodology I have ever seen. We enjoyed ourselves a lot while working together. Working with Omdena was a jubilant experience.
What I learned
We worked on real-world problems that were going to impact lots of people in Kenya. Technically I gained practical knowledge about the on-field working of Machine Learning, Deep Learning with new tools, and tools such as Activeloop, Google Colab, AWS, and more.
Many thanks to Omdena for providing me an opportunity to upskill with practical experiences and believing in me. A big thanks to all my teammates, I have learned a lot from you and managed to get promoted to a Lead Machine Learning Engineer for the next project.
