K-Means Clustering 101: World Happiness Report
Offered By: Coursera Project Network via Coursera
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
Related Courses
Social Network AnalysisUniversity of Michigan via Coursera Intro to Algorithms
Udacity Data Analysis
Johns Hopkins University via Coursera Computing for Data Analysis
Johns Hopkins University via Coursera Health in Numbers: Quantitative Methods in Clinical & Public Health Research
Harvard University via edX