The project involves using data from the World Happiness Report in applications related to data analysis, data science, data mining as well as utilizing machine learning methods, including supervised learning (regression) and unsupervised learning (clustering).
The World Happiness Report is an annual publication produced by the United Nations Sustainable Development Solutions Network, which ranks countries based on various factors related to happiness and well-being. The report is based on data collected from surveys and other sources that measure the quality of life, social support, freedom, corruption, and other factors that contribute to happiness. The report aims to provide policymakers with insights into the factors that drive happiness and well-being in different countries, and to encourage public debate and policy action on these issues.
Report and datasets are available at: https://worldhappiness.report/
Try it out with binder:
World Map - Logged GDP 2021
Comparing different regression algorithms
Random forest regression
Support vector regression (SVR)
Decision tree regression
K-means clustering
Density-based spatial clustering of applications with noise (DBSCAN)
C-means clustering (Fuzzy clustering)