Given some observed data, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution. First of all, we introduce the likelihood function of the assumed probability function. By maximizing the likelihood function, the observed data are the most probable outcome from the estimated probability distribution. The logic of maximum likelihood is intuitive and flexible and becomes a dominant means in statistics with strong impacts to modern machine learning.
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