Lecture

Linear Models: Classification

In course

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Description

This lecture covers linear models for classification, including binary classification as regression, logistic regression, decision boundaries, and support vector machines. It also discusses multi-class classification, one-hot encodings, and the application of linear models to real datasets. The instructor explains the drawbacks of least-square classification, the gradient descent algorithm, and the comparison of linear classifiers using practical examples.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_8x1q48qj

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis, Statistical classification

Information engineering

Machine learning: Topics in machine learning, Artificial neural networks

Mathematics

Algebra: Linear algebra

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