Deep Learning Indaba
| Deep Learning Indaba | |
|---|---|
| Status | Active |
| Genre | Conference |
| Location(s) | Various |
| Inaugurated | 2017 |
| Most recent | 2024 |
| Previous event | Deep Learning Indaba 2024 |
| Next event | Deep Learning Indaba 2025 |
| Organised by | Local volunteer teams |
| Filing status | Non-profit |
| Website | deeplearningindaba |
The Deep Learning Indaba is an annual conference and educational event that aims to strengthen machine learning and artificial intelligence (AI) capacity across Africa. Launched in 2017, it brings together students, researchers, industry practitioners, and policymakers from across the African continent.[1][2]
History
[edit]The Deep Learning Indaba began in 2017 at the University of the Witwatersrand with over 300 participants from 23 African countries, offering tutorials in advanced AI topics and featuring notable speakers like Nando de Freitas[3][4]. In 2018, it expanded to 650 delegates at Stellenbosch University, introducing parallel sessions to encourage collaboration. The 2019 edition in Nairobi, Kenya, reflected further growth, with increasing sponsorship and support from major tech companies like Google and Microsoft.
| Year | Host Country | Venue |
|---|---|---|
| 2017 | Johannesburg, South Africa | Wits University |
| 2018 | Stellenbosch, South Africa | Stellenbosch University |
| 2019 | Nairobi, Kenya | Kenyatta University |
| 2020 | Cancelled | Cancelled due to Covid 19 |
| 2021 | Multiple countries | Indaba X ( multiple venues) |
| 2022 | Tunis, Tunisia | Sup’Com |
| 2023 | Accra, Ghana | University of Ghana[5] |
| 2024 | Dakar, Senegal | Amadou Mahtar Mbow University (UAM) |
| 2025 | Kigali, Rwanda | University of Rwanda |
Reference
[edit]- ^ https://www.wits.ac.za/future/stories/wits-to-host-first-deep-learning-indaba-in-africa.html
- ^ https://www.up.ac.za/faculty-of-engineering-built-environment-it/news/post_2848423-go-tsamaya-ke-go-bona-deep-learning-3-a-journey-just-beginning?
- ^ https://dl.acm.org/doi/abs/10.1145/3178422.3178427
- ^ file:///C:/Users/DELL/Downloads/9780198879152_WEB%20(1).pdf
- ^ https://github.com/deep-learning-indaba/indaba-pracs-2023