Coursera Plus Annual is 40% Off — Ends July 13.

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Dimensionality Reduction: Rank-k Approximation and Eigen-decomposition - Lecture 20

UofU Data Science via YouTube

Start learning Write review
Simplilearn Ad

Lead AI-Native Products with Microsoft's Agentic AI Program

Learn More → DataCamp Ad

AI Engineer - Learn how to integrate AI into software applications

Learn More →

Overview

Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
Learn advanced dimensionality reduction techniques in this university lecture covering rank-k approximation methods, their connection to eigendecomposition, and the power method algorithm for finding dominant eigenvalues and eigenvectors in large matrices.

Syllabus

FoDA F22 Lecture 20

Taught by

UofU Data Science

Reviews

Start your review of Dimensionality Reduction: Rank-k Approximation and Eigen-decomposition - Lecture 20

Start learning

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.