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Maximum a Posteriori (MAP) estimation is a statistical technique used in the context of Bayesian inference. It provides a method for estimating an unknown parameter by maximizing the posterior distribution of that parameter, given observed data. Here’s a breakdown of the concept: 1. **Bayesian Framework**: In Bayesian statistics, we start with a prior belief about a parameter, expressed as a prior probability distribution \( P(\theta) \).

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