Introduction to Machine Learning Safety ยง
I have organized a seminar series on the safety and reliability of machine-learning systems. The course connects technical failure modes with the methods used to evaluate and mitigate them.
The lecture sequence covers:
- Introduction and motivation
- Machine-learning fundamentals
- Model testing and validation
- Adversarial machine learning
- Uncertainty quantification
- Explainability
- Anomaly and out-of-distribution detection
- AI alignment and long-term risks
The materials are intended as an accessible map of the field and may be reused with attribution. For teaching-related questions, please get in touch.