K-Means 8x faster, 27x lower error than Scikit-learn in 25 lines by Jakub Adamczyk via @kdnuggets

K-means clustering is a powerful algorithm for similarity searches, and Facebook AI Research's faiss library is turning out to be a speed champion. With only a handful of lines of code shared in this demonstration, faiss outperforms the implementation in scikit-learn in speed and accuracy.

Definitely, a new one to try and see if you like the results better.

Machine Learning Algorithms: Which One to Choose for Your Problem by Daniil Korbut via @statsbotco

Intuition of using different kinds of algorithms in different tasks.

I like this as it clearly explains which machine learning algorithm to use.

Automatically Segmenting Data With Clustering by @bilalmahmood via @kdnuggets

In this post, the author walks through one such algorithm called K-Means Clustering, how to measure its efficacy, and how to choose the sets of segments you generate.

Useful and worth reading even if you already know this just to make sure you are clear on it.