

[MINI] k-means clustering
10 snips Feb 20, 2015
The podcast discusses the k-means clustering algorithm and its objective of grouping data points into clusters without guidance. It explores tracking animal movements and customer segmentation using k-means clustering. The concept of clusters and centroids is explained, along with classifying new data points. The chapter covers accuracy, precision, and trade-offs in k-means clustering. Lastly, it explores clusters, head positioning, data visualization, and the application of k-means clustering in the workplace.
Chapters
Transcript
Episode notes
1 2 3 4 5
Introduction
00:00 • 3min
Analyzing animal movements and customer segmentation using k-means clustering
03:03 • 3min
Understanding Clusters and Centroids in k-means Clustering
05:45 • 3min
Accuracy, Precision, and Trade-offs in K-means Clustering
09:03 • 3min
Exploring Clusters and Data Visualization
12:19 • 2min