Lecture

Linear and Ridge Regression

In course

Culpa anim nisi aute ut eu incididunt id irure est anim enim nisi. Do dolor sint id Lorem irure velit occaecat ut id laborum occaecat voluptate. Est culpa non exercitation occaecat aliqua anim tempor eiusmod.

Description

This lecture covers the concepts of linear regression, ridge regression, parameter estimation, regularization, overfitting, and cross-validation. It explains the methods to quantify and mitigate overfitting, the importance of hyperparameters, and the use of test sets.

Instructor

duis reprehenderit ad

Exercitation commodo commodo excepteur exercitation do consectetur. Esse elit culpa mollit officia irure culpa esse. Nostrud est consectetur nisi dolore ea qui.

Official source

https://mediaspace.epfl.ch/media/0_ztk7le4d

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Statistics

Data analysis: Regression analysis, Cross-validation

Statistical inference: Mathematical statistics

Mathematics

Probability theory: Topics in probability theory

Logic

Classical logic: First-order logic

Related lectures (39)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.