Hierarchical Clustering: Customer Segmentation

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在此指导项目中,您将:

Build unsupervised learning algorithms in Python.

Create, Train, and Visualize a Hierarchical Clustering model in Python.

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

In this 1-hour long project-based course, you will learn how to use Python to implement a Hierarchical Clustering algorithm, which is also known as hierarchical cluster analysis. This type of algorithm groups objects of similar behavior into groups or clusters. The output of this model is a set of visualized clusters, where each cluster is distinct from each other cluster, and the objects within each cluster are broadly similar to each other in features. In this project, you will learn the fundamental theory and practical illustrations behind Hierarchical Clustering and learn to fit, examine, and utilize unsupervised Clustering models to examine relationships between unlabeled input features and output variables, using Python. We will walk you step-by-step into Machine Learning unsupervised problems. With every task in this project, you will expand your knowledge, develop new skills and broaden your experience in Machine Learning. Particularly, you will build a Hierarchical Clustering algorithm to apply market segmentation on a group of customers based on several features. By the end of this project, you will be able to build your own Hierarchical Clustering model and make amazing clusters of customers. In order to be successful in this project, you should just know the basics of Python and clustering algorithms.

您要培养的技能

Unsupervised LearningPython ProgrammingMachine LearningHierarchical 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. Import a dataset and needed libraries

  2. Choose the optimal number of clusters

  3. Fit our model and make predictions

  4. Visualize the clusters

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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