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K-Means Clustering 101: World Happiness Report

In this case study, we will train an unsupervised machine learning algorithm to cluster countries based on features such as economic production, social...

By Ryan Ahmed on Coursera

About This Course

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. The World Happiness Report determines the state of global happiness. The happiness scores and rankings data has been collected by asking individuals to rank their life from 0 (worst possible life) to 10 (best possible life).

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How much does K-Means Clustering 101: World Happiness Report cost?

Visit the K-Means Clustering 101: World Happiness Report course page for current pricing and available discounts.

Who teaches K-Means Clustering 101: World Happiness Report?

K-Means Clustering 101: World Happiness Report is taught by Ryan Ahmed, Coursera.

What skill level is K-Means Clustering 101: World Happiness Report for?

This course is designed for all levels learners.

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Students0
Duration5 hours
LevelAll Levels
Languageen
PlatformCoursera
InstructorRyan Ahmed