Data Science for Social Impact Research Group @ University of Pretoria
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- University of Pretoria, South Africa
- https://www.dsfsi.co.za
- @dsfsi_research
- company/dsfsi
- https://linktr.ee/dsfsi
- channel/UCuRj9LMcG-YFiT4eBt93DAg
- vukosi.marivate@cs.up.ac.za
We are the Data Science for Social Impact research group at the Computer Science Department, University of Pretoria.
Our general areas of work straddle Data Science for Society as well as Local Language Natural Language Processing. These two strands are complementary. Our work in Data Science and Society has allowed us to have a more nuanced approach to understanding the systematic challenges that face being able to do excellent science with local languages. Through Data Science for Society, we have to understand how when one carries through Data Science research, we situate how the users are part of the process. We find that we need to adjust our research to take care of these challenges and innovate in ways we gather direct data or alternative data.
For us, Data Science for Society means being able to improve approaches/methods or scientific tools for DS while enhancing the ways decision-makers can use the insights that come from these tools. Local Language Natural Language Processing is focused on ways to develop new tools, new data and methodology to improve the state of African languages.
To be a leading inclusive lab that creates and harnesses data and multidisciplinary scientific exploration for societal impact.
Data-driven collaborative innovation to empower society to tackle challenges and preserve our languages.
- Community and Collaboration
- Shared responsibility
- Inclusiveness
- Integrity and openness
- Agency
- Generosity
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Repositories
- lacunafund-datasets Public Forked from Fair-Forward/datasets
A catalog that links to the datasets and use-cases of the Lacuna Fund
dsfsi/lacunafund-datasets’s past year of commit activity - cross-lingual-transfer-gains-evaluation Public
Code and datasets for studying cross-lingual embedding transfer and transfer gain analysis in mutually intelligible African languages using VecMap and MUSE.
dsfsi/cross-lingual-transfer-gains-evaluation’s past year of commit activity - dsfsi-podcast Public
dsfsi/dsfsi-podcast’s past year of commit activity - deadlines Public Forked from vukosim/ai-ds-africa-deadlines
⏰ AI/ML/DS conference/workshop/event deadlines on the African continent
dsfsi/deadlines’s past year of commit activity - vukuzenzele-nlp Public Forked from dsfsi/dsfsi-dataset-template
The dataset contains editions from the South African government magazine Vuk'uzenzele. Data was scraped from PDFs that have been placed in the data/raw folder. The PDFS were obtained from the Vuk'uzenzele website.
dsfsi/vukuzenzele-nlp’s past year of commit activity
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