Data Mining Spring 2023 Distance

Data Mining Spring 2023 Distance Information Guide

1. Overview of Data Mining Spring 2023 Distance
2. Core Information
3. History
4. Deep Dive
5. Conclusion

Overview of Data Mining Spring 2023 Distance

0:00 Recording starts 0:44 Lecture starts 0:52 Announcements 4:07 Revisit: Prob[candidate]-similarity curves 10:32 Revist (d1,d2 ... 0:00 Recording starts 0:45 Lecture starts 0:56 Drop/Withdrawal policy 1:26 Changes to the syllabus 4:34 Clarification of Lecture 2 ... 0:00 Recording starts 0:16 Lecture starts 0:17 Announcements 3:27 Clustering (intro) 11:14 Categories of clustering algos 23:38 ... 0:00 Recording start 0:48 Lecture begins 2:16 The logistics of the course 5:05 Website (main) 9:48 Pre-requisites 15:40 Reading ... 0:00 Recording starts 0:29 Announcements 2:26 Spectral clustering (intro) 5:23 Graphs 21:34 Approx. the partitioning problem ... 0:00 Lecture starts 0:43 Best rank-k approximation (recap) 5:54 PCA vs. SVD 9:50 Random projection (motivation) 17:30 ...

0:00 Recording start 0:27 Lecture start 0:33 Announcements 2:43 k-means (intro) 8:28 k-means (formally) 17:03 Lloyd's algorithm ... 0:00 Recording starts 1:27 Lecture starts 1:55 MDS (motivation) 8:31 MDS (outline) 24:41 MDS (clarification) 39:17 LDA ...

Core Information

History

Data Mining (Spring 2023) - Class Overview

Data Mining (Spring 2023) - Spectral Clustering

Data Mining (Spring 2023) - Random Projection

Data Mining (Spring 2023) - k-means

Data Mining (Spring 2023) - Multidimensional scaling (MDS) & Linear discriminant analysis (LDA)

Data Mining Lecture L10 - Distances for Distributions

Data Mining Lecture 7 - Metric Distances

Euclidean Distance & Cosine Similarity | Introduction to Data Mining | Part 17

Deep Dive

Data is compiled from public records and verified media reports.

Last Updated: June 10, 2026

Conclusion

Disclaimer: Disclaimer: Details estimates are based on publicly available data, media reports, and financial analysis. Actual numbers may vary.