Wrapped up my Machine Learning internship of 10 weeks at Omdena where I worked on implementing various methodologies to leverage AI to map land ownership to restore degraded land in Kenya in an equitable way.
It involved extracting required information from publicly available
documents in Kenya such as government gazettes, court records,
government procurement and analyzing it using Natural Language Processing techniques and researching and analyzing the processed data to understand the political economy of natural resource management and key bottlenecks for forest and landscape restoration.
Highlights of my work -
- Creating a Knowledge Graph of land ownership in Kenya.
- Generating a list of 'Watch List' organizations to identify corruption with land ownership.
- Understanding different networks in the open-source land documents.
- Geo-tagging network data & making it easily accessible to social-activists, journalists.
It involved extracting required information from publicly available
documents in Kenya such as government gazettes, court records,
government procurement and analyzing it using Natural Language Processing techniques and researching and analyzing the processed data to understand the political economy of natural resource management and key bottlenecks for forest and landscape restoration.
Highlights of my work -
- Creating a Knowledge Graph of land ownership in Kenya.
- Generating a list of 'Watch List' organizations to identify corruption with land ownership.
- Understanding different networks in the open-source land documents.
- Geo-tagging network data & making it easily accessible to social-activists, journalists.
