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Uncertainty in deep learning models
- Uncertainty in deep learning models can arise from randomness or inherent noise in the dataset.
- The uncertainty cannot be reduced with more data collection.
- There are two types of uncertainty in deep learning models - Aleatoric uncertainty and Epistemic uncertainty.
- Aleatoric uncertainty is due to randomness or noise in the dataset, while Epistemic uncertainty represents the model's lack of knowledge.
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