Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Expectation propagation (EP) is a technique in Bayesian machine learning, developed by Thomas Minka. EP finds approximations to a probability distribution. It uses an iterative approach that leverages the factorization structure of the target distribution. It differs from other Bayesian approximation approaches such as Variational Bayesian methods. Machine learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases.

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