Quantifying Model Uncertainty

Christoph emphasizes the need to quantify uncertainty in machine learning models, highlighting the importance of not just providing a single number or explanation but also understanding the distribution and variance behind it. He discusses the lack of quantification of uncertainty in current methods and the necessity of incorporating confidence intervals for better interpretability.