Linear Models: Classification

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Covers linear models for multi-class classification, focusing on logistic regression and evaluation metrics.

Explores the extension of linear classifiers to handle multiclass problems and compares their performance on various datasets.

Explores linear models for classification, including binary classification, logistic regression, decision boundaries, and support vector machines.

Covers linear models for classification, focusing on logistic regression and support vector machines.

Explores linear models for classification, logistic regression, decision boundaries, SVM, multi-class classification, and practical applications.

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

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, SVM, k-NN, and curse of dimensionality.

Explores linear models, logistic regression, classification metrics, SVM, and their practical use in data science methods.