In this case study, we will train an unsupervised machine learning algorithm to cluster countries based on features such as economic production, social support, life expectancy, freedom, absence of corruption, and generosity.

您将学到什么
Understand how to leverage the power of machine learning to perform unsupervised segmentation
Learn how to use Plotly to visualize geographical data
Learn how to obtain the optimal number of clusters using the elbow method
您将练习的技能
要了解的详细信息

添加到您的领英档案
仅桌面可用
了解顶级公司的员工如何掌握热门技能

在 2 小时内学习、练习并应用岗位必备技能
- 接受行业专家的培训
- 获得解决实训工作任务的实践经验
- 使用最新的工具和技术来建立信心

关于此指导项目
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:
-
Understand the problem statement and business case
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Import datasets and libraries
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Perform exploratory data analysis
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Perform data visualization - part 1
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Perform data visualization - part 1
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Prepare the data to feed the clustering model
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Understand the intuition behind k-means clustering algorithm
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Find the optimal number of clusters
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Apply k-means using scikit-learn to perform segmentation
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Visualize the clusters
推荐体验
Basic python programming and mathematics.
8个项目图片
位教师

提供方
学习方式
基于技能的实践学习
通过完成与工作相关的任务来练习新技能。
专家指导
使用独特的并排界面,按照预先录制的专家视频操作。
无需下载或安装
在预配置的云工作空间中访问所需的工具和资源。
仅在台式计算机上可用
此指导项目专为具有可靠互联网连接的笔记本电脑或台式计算机而设计,而不是移动设备。
人们为什么选择 Coursera 来帮助自己实现职业发展

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学生评论
- 5 stars
71.42%
- 4 stars
28.57%
- 3 stars
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显示 3/21 个
已于 Sep 16, 2025审阅
Gain maximum information in relative short period of time.
已于 Dec 17, 2022审阅
I learned a lot during this guided project.Thank you very muchAkash Bhat
已于 May 29, 2022审阅
Good project to learn K-Means, good instructor, very comprehensive slides and interesting dataset. Basic Python knowledge needed.







