The poster-child for unsupervised learning problem is k-means clustering. In 6 words: partition N datapoints into K clusters. That simple idea is worth an entire season of Data Skeptic. In this first episode, Kyle sets down some foundational details and overviews key concepts related to k-means clustering and it’s most famous approach: Lloyd’s Algorithm.