Uncertainty
Uncertainty refers to the lack of knowledge or information about the future outcomes of a particular event or situation. In data science and artificial intelligence, uncertainty is a common issue that arises due to incomplete or noisy data, model inaccuracies, and other factors. Uncertainty can be classified into two types: aleatoric and epistemic. Aleatoric uncertainty is related to the inherent randomness or variability in the data, while epistemic uncertainty is related to the lack of knowledge or understanding of the underlying system or model. Uncertainty can be quantified using various techniques such as probability theory, Bayesian inference, and Monte Carlo simulations. Managing uncertainty is crucial in decision-making processes, especially in high-stakes applications such as healthcare, finance, and autonomous systems.
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