This repository is a professionally maintained awesome list aggregating videos, tutorials, papers, books, and open-source libraries on conformal prediction. Conformal prediction provides distribution-free, model-agnostic uncertainty quantification by returning prediction sets or intervals with guaranteed coverage. The list explicitly covers applications to large language models, deep neural networks, time series forecasting, and robust ML.