Supporting Food Security in Africa Using ML with Catherine Nakalembe - #611
Published:Jan 9, 2023 20:17
•1 min read
•Practical AI
Analysis
This article summarizes a podcast episode from Practical AI featuring Catherine Nakalembe, discussing her work on using machine learning and earth observations to support food security in Africa. The episode focuses on the challenges and solutions related to food insecurity, Nakalembe's role as Africa Program Director under NASA Harvest, and the technical hurdles she faces. These include limited access to remote sensing data, the lack of benchmarks, and the application of techniques like multi-task learning. The article highlights the importance of satellite-driven methods for agricultural assessments and the ongoing efforts to improve food security in Africa.
Key Takeaways
- •Machine learning and earth observations are being used to address food insecurity in Africa.
- •NASA Harvest Africa program is developing satellite-driven methods for agricultural assessments.
- •Technical challenges include limited data access and the need for benchmarks.
Reference
“We take a deep dive into her talk from the ML in the Physical Sciences workshop, Supporting Food Security in Africa using Machine Learning and Earth Observations.”