The objective of this competition is to create a machine learning model to help Kenyan non-profit organization Local Ocean Conservation identify potential errors and anomalies in their sea turtle rescue database from their By-Catch Release Programme. The data used to train the model will be ‘dirty’ and ‘cleaned’ data containing all of the unique sea turtle rescues that took place from 1998 until 2011. To date, Local Ocean Conservation has released over 10,000 sea turtles.
A machine learning solution to help identify erroneous fields in the datasets will be a huge enabler for Local Ocean Conservation. It will allow the organization to rapidly clean the remaining years of ‘dirty data’ - fast-tracking the team's ability to use that data for accurate analysis, academic research, and ultimately effective conservation work. Currently, this is a very laborious task requiring significant time from the team, preventing them from working on critical work and important conservation efforts.
This competition is sponsored by Local Ocean Conservation, Temple Point Resort, and individual donors of Local Ocean Conservation.
About Local Ocean Conservation (LOC) (localocean.co):
LOC is a private, not-for-profit organisation committed to the protection of Kenya’s marine environment. LOC supports the communities and coastal areas in Watamu and Diani, Kilifi County with marine conservation and community development projects – centred around a holistic approach to conservation. LOC has been doing marine conservation for over 20yrs.
About Temple Point Resort (www.templepointresort.com):
The Temple Point Resort is a premier holiday beach resort located at the end of a headland between the Indian Ocean and Mida Creek. Surrounded by tropical gardens and the Mida Creek lagoon, the hotel is situated right inside the Watamu Marine National Park. Conveying the atmosphere of a delightful private home with luxurious accommodation, the resort standards are designed to provide the highest quality venue for both individual holiday makers and corporate functions.