Unsupervised Machine Learning for Customer Market Segmentation

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在此指導項目中,您將:

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初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this hands-on guided project, 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 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.

您要培養的技能

  • Artificial Intelligence (AI)
  • Machine Learning
  • clustering
  • Python Programming
  • unsupervised machine learning

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

授課教師

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