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K-Means Clustering 101: World Happiness Report

Offered By: Coursera Project Network via Coursera

Tags

Unsupervised Learning Courses Data Analysis Courses Machine Learning Courses Generosity Courses

Course Description

Overview

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).

Syllabus

  • Clustering: 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 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).

Taught by

Ryan Ahmed

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