CS 1110 Fall 2024
Machine Learning is a major computer science topic these days. And while it can seem really powerful, it is often just the application of statistics to large amounts of data. As computers become both ubiquitous and more powerful, many applications — from science to business to entertainment — are generating huge amounts of data. In this assignment you will work with one of the most popular (though not necessarily most efficient) tools for analyzing large amounts of data: k-means clustering. In k-means clustering, you organize the data into a small number (k) of clusters of similar values. For example, in the picture to the right, there are a lot of points in 3-dimensional space. These points are color-coded into five clusters, with all the points in a cluster being near to one another. If you look at the wikipedia entry for k-means clustering, you can see that it has many, many applications. It has been used in market analysis, recommender systems (e.g. how Netflix recommends new movie
Machine Learning is a major computer science topic these days. And while it can seem really powerful, it is often just the application of statistics to large amounts of data. As computers become both ubiquitous and more powerful, many applications — from science to business to entertainment — are generating huge amounts of data. In this assignment you will work with one of the most popular (though not necessarily most efficient) tools for analyzing large amounts of data: k-means clustering . In k-means clustering, you organize the data into a small number (k) of clusters of similar values. For
related reading
- A Course in Machine Learningciml.info
- Machine Learning, Kolmogorov Complexity, and Squishy Bunniestheorangeduck.com
- CS231n Deep Learning for Computer Visioncs231n.github.io
- How to Determine the Optimal K for K-Means? | by Khyati Mahendru | Analytics Vidhya | Mediummedium.com
- k-means clustering - Wikipediaen.wikipedia.org
- CSC 151 - A computer scientist's perspective on data scienceeikmeier.sites.grinnell.edu
- How to cluster images based on visual similarity | Towards Data Sciencetowardsdatascience.com
- 6.036_notes.pdfphillipi.github.io
- Clustering Algorithms: K-Means, EMC and Affinity Propagation | Toptal®toptal.com
- kMeans: Initialization Strategies- kmeans++, Forgy, Random Partition | Analytics Vidhyamedium.com
- deeplearningbook.org/contents/ml.htmldeeplearningbook.org
- CS124 - From Languages to Information (Winter 2026)web.stanford.edu