Hierarchical Clustering: Customer Segmentation

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このガイド付きプロジェクトでは、次のことを行います。

Build unsupervised learning algorithms in Python.

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

Clock2 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

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.

あなたが開発するスキル

Unsupervised LearningPython ProgrammingMachine LearningHierarchical Clustering

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. Import a dataset and needed libraries

  2. Choose the optimal number of clusters

  3. Fit our model and make predictions

  4. Visualize the clusters

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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