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This lecture continues the exploration of linear models, focusing on hyperplanes, linear regression, matrix form, multi-output prediction, and classification evaluation. It delves into logistic regression, gradient descent, and multi-class logistic regression, with practical applications and examples. The instructor demonstrates the training process, gradient computation, and prediction in logistic regression. The lecture concludes with decision boundaries and interpreting linear models.