Introduction to Customer Segmentation in Python

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Coursera Project Network
在此指导项目中,您将:

Dimensionality Reduction using standard PCA and variants

Create interactive plots

Clustering data using K-Means with evaluation metrics

Clock2 hours
Beginner初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

  • Dimensionality Reduction
  • Market Segmentation
  • Machine Learning
  • clustering

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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