Interpretable Active Learning

This course on interpretable active learning aims to teach learners the concepts and techniques related to making machine learning models more interpretable. The course covers the Lime method and its application in active learning. The teaching method involves a lecture format with a duration of 21 minutes. This course is intended for individuals interested in the intersection of machine learning and interpretability, particularly those looking to enhance the transparency and understanding of their machine learning models.