Newsletter #2: k-means clustering

Learning resources for k-means, an important tool in machine learning.

Welcome to the second issue of the Aleph 0 newsletter! This issue, we’re covering k-means clustering, an important tool in machine learning and data analysis.

Learning Resources

The k-means clustering method is an unsupervised learning technique used to identify clusters of objects in a dataset. There are many different techniques used to identify clusters in data, but k-means is one of the simplest to describe.

• Here’s a very clear video explainer by Victor Lavrenko:

• Here’s a written explanation by 365 data science: https://365datascience.com/tutorials/python-tutorials/k-means-clustering/

• Check this helpful visualization of k-means: http://shabal.in/visuals/kmeans/6.html

Challenge Problem

A solution will be revealed in the next issue.

Here is the solution to last week’s problem. Thanks to all of you who submitted an answer to the problem!

Feedback

If you have a solution to the above challenge problem, submit it here for a chance to be featured in the next issue of this newsletter.

If you have any learning resources that you think would be valuable for readers, or if you have any general feedback, let me know here and I’d be happy to incorporate it.

Thanks for reading and happy learning! Until next time,
Adithya