Lectures, Slides and Videos
Keynotes
Tutorial Lectures
Special Sessions
- Deep Learning: The AI Revolution and its Frontiers, Nando de Freitas [Slides]
- Success Stories of Reinforcement Learning, David Silver [Slides]
- Principles of Reinforcement Learning, David Silver [Slides]
- Tensorflow and Real-world Machine Learning, Jeff Dean
Tutorial Lectures
- Mathematics for Machine Learning (Avishkar Bhoopchand, Cynthia Mulenga, Daniela Massiceti, Kathleen Siminyu, Kendi Muchungi) - [slides | lecture notes ]
- Deep Learning Fundamentals, Moustapha Cisse [Slides]
- Convolutional Models, Naila Murray [Slides (pdf) | Slides (ppt)]
- Probabilistic Thinking, Yabebal Fantaye [Slides (pdf)]
- Recurrent Neural Networks, Kyunghyun Cho [Slides (pptx)]
- Generative Models, Shakir Mohamed [Slides (pdf)]
- Reinforcement Learning, Katja Hofmann [Slides (pdf, no video)| Slides (ppt, with videos)]
Special Sessions
- Non-recurrent sequence models
- Frontiers of Computer Vision
- Daniela Massiceti, Sara Hooker, Saumya Jetley [Slides | Spotlights]
- AI for Africa
- Machine Learning and Healthcare
- Konstantina Palla [Slides]
- Natural Language Processing - [Slides (pdf)]
- Life of a Startup
- Reinforcement Learning
- Machine Learning in Production
- AI Ethics and Policy
- Algorithmic Systems: Ethics Considerations, Osonde Osoba [Slides (ppt)]
- Understanding the Limits of AI: When Algorithms Fail, Timnit Gebru [Slides (ppt)]
Practicals
- Github repository of all practicals; can be opened using Colab.