Maximum Likelihood Estimation
Maximum Likelihood Estimation (MLE) is a statistical method used to estimate the parameters of a probability distribution by maximizing the likelihood function. In other words, MLE is a technique used to find the values of the parameters that make the observed data most probable. The likelihood function is a function of the parameters of the distribution and the observed data. The maximum likelihood estimate is the set of parameter values that maximize the likelihood function. MLE is widely used in machine learning, data science, and artificial intelligence to estimate the parameters of models such as linear regression, logistic regression, and neural networks.
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