Speaker
Olivier Colliot
Description
Goal: Introduce the basics of ML and describe in details how to perform validation
- History and terminology
- Problem setup for ML basics (Model, loss, learning procedure, features)
- Generalization in ML (overfitting, underfitting and model selection)
- Validation (performance metrics, validation strategies, statistical analysis)