- Course
Introduction to Clustering in Python
Customer data can reveal useful patterns in purchasing behavior. This course will teach you to prepare and scale features, group customers with k-means in Python, compare cluster counts, and explain the resulting segments in business terms.
Intermediate
- Course
Introduction to Clustering in Python
Customer data can reveal useful patterns in purchasing behavior. This course will teach you to prepare and scale features, group customers with k-means in Python, compare cluster counts, and explain the resulting segments in business terms.
Intermediate
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This course is included in the libraries shown below:
- Data
What you'll learn
Unlabeled customer data can hide useful differences in behavior. In this course, Introduction to Clustering in Python, you’ll gain the ability to find and explain groups with a repeatable clustering workflow. First, you’ll explore how similarity, features, and unsupervised learning shape a grouping problem. Next, you’ll discover how to select and scale features and build k-means models. Finally, you’ll learn how to compare cluster counts and interpret segment profiles. When you’re finished with this course, you’ll have the skills and knowledge of clustering in Python needed to turn unlabeled observations into carefully qualified analytical findings.
Introduction to Clustering in Python
Intermediate
Table of contents
Pinal Dave is a Pluralsight Developer Evangelist.
