Introduction to Customer Segmentation in Python

4.6
13 個評分
提供方
Coursera Project Network
在此指導項目中,您將:

Dimensionality Reduction using standard PCA and variants

Create interactive plots

Clustering data using K-Means with evaluation metrics

Clock2 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this 2 hour long project, you will learn how to approach a customer purchase dataset, and how to explore the intricacies of such a dataset. You will learn the basic underlying ideas behind Principal Component Analysis, Kernel Principal Component Analysis, and K-Means Clustering. You will learn how to leverage these concepts, paired with industry knowledge and auxiliary modeling concepts to segment the customers of a certain store, and find similarities and differences between different clusters using unsupervised machine learning techniques. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培養的技能

  • Dimensionality Reduction
  • Market Segmentation
  • Machine Learning
  • clustering

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Introduction to the task and demo

  2. Exploratory Data Analysis

  3. Principal Component Analysis

  4. Kernel Principal Component Analysis

  5. K-Means Clustering

  6. Interactive Cluster Analysis

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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