Hands-On Unsupervised Learning Using Python

Part II. Unsupervised Learning Using Scikit-Learn

In the next few chapters, we will introduce two major unsupervised learning concepts—dimensionality reduction and clustering—and use these to perform anomaly detection and group segmentation.

Both anomaly detection and group segmentation have significant real-world applications across many different industries.

Anomaly detection is used to efficiently discover rare events such as fraud; cybersecurity breaches; terrorism; human, arms, and drug trafficking; money laundering; abnormal trading activity; disease outbreaks; and maintenance failures in mission-critical equipment.

Group segmentation allows us to understand user behavior in areas such as marketing, online shopping, music listening, video watching, online dating, and social media activity, among others.