Back to ListHuman-Centred Machine Learning
Level
Intermediate, Broad, Theory, Algorithmic.
This topic covers methods to develop Human-Aware ML algorithms and models.
Learning outcomes
Content /Knowledge
Student should be able to:
- Understand the adaptation of the Machine Learning and Transformers architectures to deal with audio, text and visual data.
- Grasp the functioning principles of recent work applying Transformers architecture to multimodal tasks and data.
- Be aware of the human interventions in interactive machine learning .
- Understand human teaching strategies and gain knowledge about learning from human feedback, demonstrations and instructions.
Methodologicalskills
Students should be able to:
- Define computational models of human teaching strategies.
Transferrable/Application
Students should be able to:
- Discuss applications of human-centered machine learning.