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试用DataCamp for Business课程描述
先决条件
Supervised Learning with scikit-learn1
Cohort Analysis
In this first chapter, you will learn about cohorts and how to analyze them. You will create your own customer cohorts, get some metrics and visualize your results.
2
Recency, Frequency, and Monetary Value Analysis
In this second chapter, you will learn about customer segments. Specifically, you will get exposure to recency, frequency and monetary value, create customer segments based on these concepts, and analyze your results.
3
Data Preprocessing for Clustering
Once you created some segments, you want to make predictions. However, you first need to master practical data preparation methods to ensure your k-means clustering algorithm will uncover well-separated, sensible segments.
4
Customer Segmentation with K-means
In this final chapter, you will use the data you pre-processed in Chapter 3 to identify customer clusters based on their recency, frequency, and monetary value.
Customer Segmentation in Python
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