Expectation Maximization: how it works

Full lecture: http://bit.ly/EM-alg We run through a couple of iterations of the EM algorithm for a mixture model with two univariate Gaussians. We initialise the Gaussian means and variances with random values, then compute the posterior probabilities for each data point, and use the posteriors to re-estimate the means and variances.

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