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Measuring the cross-entropy loss contribution of this single image during a training epoch.

Generating Grad-CAM visualizations to identify which pixels the model focuses on when classifying this specific image. 3. Results & Discussion 148_1000.jpg

Recommendations for automated "cleaning" of datasets based on high-loss samples. Measuring the cross-entropy loss contribution of this single

Applying t-SNE or UMAP to see where this image sits relative to its assigned class. 148_1000.jpg

Testing how minor augmentations (rotations, color jitters) to this image change the model's confidence. 4. Conclusion

1. Introduction

Summary of how individual data point audits can lead to more robust AI models.