Objectives
After learning about fundamental data analysis techniques from the prerequisite courses, this course goes deeper into techniques for building trustworthy artificial intelligence (AI) by rigorous performance estimation with modern resampling methods. The core aim is to adopt a scientific way of thinking on the evaluation design for machine learning based AI systems, namely how to answer to more specific statistical questions regarding prediction performance evaluation that go beyond the usual generalization to unseen data, such as how well the AI system works with new data given that the new data is known to differ from the already observed training data in a specific way.
- Opettaja
Tapio Pahikkala