Customer Segmentation using K-Means Clustering in R

提供:
Coursera Project Network
このガイド付きプロジェクトでは、次のことを行います。

Understand the intuition behind the K-Means Clustering algorithm

Create plots of the customer features

Create plots of the distinct customer segments based on features

Clock2.5 hours
Intermediate中級
Cloudダウンロード不要
Video分割画面ビデオ
Comment Dots英語
Laptopデスクトップのみ

Welcome to this project-based course, Customer Segmentation using K-Means Clustering in R. In this project, you will learn how to perform customer market segmentation on mall customers data using different R packages. By the end of this 2-and-a-half-hour long project, you will understand how to get the mall customers data into your RStudio workspace and explore the data. By extension, you will learn how to use the ggplot2 package to render beautiful plots of the data. Also, you will learn how to get the optimal number of clusters for the customers' segments and use K-Means to create distinct groups of customers based on their characteristics. Finally, you will learn how to use the R markdown file to organise your work and how to knit your code into an HTML document for publishing. Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Customer Segmentation. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!

あなたが開発するスキル

  • clustering
  • Ggplot2
  • K-Means Clustering
  • PCA
  • unsupervised machine learning

ステップバイステップで学習します

ワークエリアを使用した分割画面で再生するビデオでは、講師がこれらの手順を説明します。

  1. Getting Started

  2. Import and Explore the Data

  3. Data Visualization - Part One

  4. Data Visualization - Part Two

  5. Understand the concept of K-Means

  6. Determine the number of Clusters

  7. K-Means Clustering

  8. Principal Component Analysis

  9. Plot the K-Means Segments

ガイド付きプロジェクトの仕組み

ワークスペースは、ブラウザに完全にロードされたクラウドデスクトップですので、ダウンロードは不要です

分割画面のビデオで、講師が手順ごとにガイドします

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