Binary Responses: Link Functions and GLMs

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Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.

Explores logistic regression for binary response variables, covering topics such as odds ratio interpretation and model fitting.

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Covers the analysis of chimpanzee data on learning times and explores generalized linear models and logistic regression.

Covers linear models, binary classification, logistic regression, and model evaluation metrics.

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Covers logistic regression, probabilistic interpretation, and feature engineering techniques.

Covers linear models for classification, logistic regression training, evaluation metrics, and decision boundaries.

Explores linear models, logistic regression, gradient descent, and multi-class logistic regression with practical applications and examples.

Explores linear models for classification, logistic regression, and gradient descent in machine learning.