Bayes' Theorem is a fundamental principle in probability theory that describes how to update the probability of a hypothesis based on new evidence. This theorem connects conditional probability with prior knowledge, allowing one to calculate the likelihood of an event given previous conditions. It emphasizes the importance of revising predictions or beliefs when faced with new data, showcasing its utility in various fields such as finance, medicine, and machine learning.
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