Logistic regression is a statistical model that predicts the probability that a random variable belongs to a certain category or class. In this video we use the Sigmoid function to form our hypothesis (statistical model). After that we form our likelihood function as a Bernoulli distribution given a data set, and using the maximum likelihood estimation method the model parameters are estimated using the gradient ascent algorithm.
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