Chapter 7: Clustering Using the K-Means Algorithm
In this chapter, we'll introduce unsupervised machine learning, and you'll learn how to use BigQuery ML to build K-Means algorithms to cluster similar data into multiple categories.
Unsupervised machine learning is particularly useful when we have datasets without any labels, and we need to infer the structure of the data without any initial knowledge.
In different industries, it can be very valuable to identify similar events, objects, and people according to a specific set of features. K-Means clustering is typically used to identify similar customers, documents, products, events, or items according to a specific set of characteristics.
In this chapter, we'll focus our attention on the K-Means clustering algorithm, which is widely used to reveal similarities in structured and unstructured data. We'll go through all the steps required to build a K-Means clustering model, leveraging BigQuery ML.
With...
