K Means Clustering for Imagery Analysis

In this project, we will use a K-means algorithm to perform image classification. Clustering isn't limited to the consumer information and population sciences, it can be used for imagery analysis as well. Leveraging Scikit-learn and the MNIST dataset, we will investigate the use of K-means clustering for computer vision.

In this project, we will learn how to:

  • Preprocess images for clustering
  • Deploy K-means clustering algorithms
  • Use common metrics to evaluate cluster performance
  • Visualize high-dimensional cluster centroids