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DataCamp for Business 체험강의 설명
선수 조건
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.
Python을 활용한 고객 세분화
강의 완료
DataCamp for Mobile을 통해 데이터 분석 능력을 향상시키세요.
모바일 강좌와 매일 5분 코딩 챌린지를 통해 이동 중에도 학습 효과를 높이세요.