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This document discusses vectorizing the computations in logistic regression. It shows the vectorized equations for the logistic regression model, where z is the linear combination of weights and inputs, and a is the activation calculated by applying the sigmoid function to z. It then outlines the vectorized implementation of computing the cost function J and its partial derivatives with respect to the weights and bias, which are calculated by summing the individual contributions from each training example.

Author

JoseLuis López Molano

Language

EN