教程:用于客户市场细分的无监督机器学习

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在此指导 教程中,您将:

Understand how to leverage the power of machine learning to transform marketing departments and perform customer segmentation

Compile and fit unsupervised machine learning models such as PCA and K-Means to training data.

Understand the theory and intuition behind Principal Component Analysis (PCA) and k-means clustering machine learning algorithm

Learn how to obtain the optimal number of clusters using the elbow method

Clock1 hour
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 guided tutorial, we will train unsupervised machine learning algorithms to perform customer market segmentation. Market segmentation is crucial for marketers since it enables them to launch targeted ad marketing campaigns that are tailored to customer's specific needs. Note: This tutorial 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

Artificial Intelligence (AI)Machine LearningclusteringPython Programmingunsupervised machine learning

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. Understand the problem statement and business case

  2. Import libraries and datasets

  3. Visualize and explore datasets

  4. Understand the theory and intuition behind k-means clustering machine learning algorithm

  5. Learn how to obtain the optimal number of clusters using the elbow method

  6. Use Scikit-Learn library to find the optimal number of clusters using elbow method

  7. Apply k-means using Scikit-Learn to perform customer segmentation

  8. Apply Principal Component Analysis (PCA) technique to perform dimensionality reduction and data visualization

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