Lecture

Statistical Learning: Fundamentals

In course

Nisi officia in incididunt aliquip elit veniam est nulla qui labore qui id. Id quis laborum ea ullamco culpa proident. Aute amet sit cupidatat nulla. Adipisicing aute occaecat qui irure nulla dolore magna laboris dolore culpa et consectetur dolore. Culpa id officia ex nulla consectetur amet id. Do aliqua laboris consectetur id nisi nulla officia veniam dolor in sunt. Sint nostrud consectetur fugiat eiusmod do sit officia ut Lorem.

Description

This lecture covers the basics of statistical learning, including different types of learning settings, supervised learning formalization, decision theoretic framework, risk minimization, and overfitting symptoms. It also delves into key concepts such as Tikhonov regularization, polynomial regression, dimensionality reduction, SVMs, neural networks, and ethical considerations in machine learning.

This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.

Watch on Mediaspace

Official source

https://mediaspace.epfl.ch/media/0_tqx75vjo

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: Cross-validation, Regression analysis

Information engineering

Machine learning: Artificial neural networks

Energy engineering

Nuclear power: Topics in nuclear power

Related lectures (118)

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.