Tutorials#
- The Workflows of Data-centric AI for Classification with Noisy Labels
- Understanding Dataset-level Labeling Issues
- Detect Outliers with Cleanlab and PyTorch Image Models (timm)
- Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators
- Find Label Errors in Multi-Label Classification Datasets
- Find Noisy Labels in Regression Datasets
- Find Label Errors in Token Classification (Text) Datasets
- Find Label Errors in Semantic Segmentation Datasets
- Finding Label Errors in Object Detection Datasets
- Computing Out-of-Sample Predicted Probabilities with Cross-Validation
- FAQ