教程：用于客户市场细分的无监督机器学习
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
中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.
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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：
Understand the problem statement and business case
Import libraries and datasets
Visualize and explore datasets
Understand the theory and intuition behind k-means clustering machine learning algorithm
Learn how to obtain the optimal number of clusters using the elbow method
Use Scikit-Learn library to find the optimal number of clusters using elbow method
Apply k-means using Scikit-Learn to perform customer segmentation
Apply Principal Component Analysis (PCA) technique to perform dimensionality reduction and data visualization
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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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来自教程：用于客户市场细分的无监督机器学习的热门评论
best practical course to understand unsupervised learning.faculty was precise and clear hoping to complete other courses from the faculty
Wonderful course to understand clustering basics. Ryan teaches the concepts as well as gives hands on practice in a very simplified way.
This project is quite explanatory and fun. Thanks to Ryan Ahmed and Coursera.....now I'm good to go on Customer Market Segmentation.
One of the best guided projects I have done so far. The instructor does their best in teaching what each part of the code entails.
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