Bayes’ Theorem In Artificial Intelligence
Bayes’ Theorem has been a central component of discussing the effects and influences of solving conditional probability. However Bayes’ Theorem can be used in various industries to solve many different types of problems in an array of fields. In probability theory, it relates the conditional probability and the marginal probabilities of two random events. In statistics, the Bayesian inference is an application of Bayes’ theorem and a core component of a different type of statistics. Further, it is also a central driver of finding solutions to problems faced in Artificial Intelligence.
In the article attached, it discusses the Application of Bayes’ theorem in Artificial intelligence. Things like: calculating the next step of the robot when the already executed step is given. In weather forecasting Artificial Intelligence algorithms, and the ability to solve the Monty Hall Problem(a popular mathematical problem that shows using new information to make significant decisions). Additionally, several AI based algorithms, including those for prediction, anomaly detection, diagnostics, automated insight, reasoning/logic, time series prediction, and decision-making under uncertainty, make use of the Bayes theorem.
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https://machinelearningmastery.com/bayes-theorem-for-machine-learning/