Linear Regression: Statistical Inference and Regularization

In course

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Description

This lecture covers the probabilistic model for linear regression, statistical inference, maximum likelihood and maximum a posteriori estimators, regularization techniques like LASSO, and the importance of variable selection in the context of machine learning.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_1y3ev0oa

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis, Cross-validation

Statistical inference: Mathematical statistics, Statistical hypothesis testing

Information engineering

Signal processing: Time–frequency analysis

Mathematics

Analysis: Functional analysis

Algebra: Linear algebra

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