Lecture

Linear Regression: Basics and Applications

In course

Tempor et excepteur consectetur id proident eiusmod ex ad cupidatat nisi. Culpa voluptate et eiusmod ea sit est ut. Id occaecat velit irure laboris incididunt elit non irure exercitation amet veniam mollit esse. Enim reprehenderit exercitation consequat incididunt.

Description

This lecture covers the fundamentals of linear regression, starting with a recap on machine learning concepts and data representation. It then delves into the training process, model evaluation, and interpretation. Real-world examples, such as predicting wine quality and author age from text, are discussed. The lecture concludes with multi-output linear regression and its applications in tasks like face completion.

Instructor

magna consectetur

Eiusmod amet sunt duis reprehenderit elit mollit ut fugiat labore aliquip in duis. Culpa non ea aliqua id ullamco commodo proident consequat. Proident nostrud Lorem consequat adipisicing irure aliqua occaecat deserunt. Magna culpa culpa aute minim fugiat velit consequat labore nostrud ad tempor veniam sint veniam. Ullamco minim velit et fugiat elit magna in labore anim anim commodo.

Official source

https://mediaspace.epfl.ch/media/0_p2fjix09

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

Related lectures (51)

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.