Data analysis and visualization of the World Happiness Report 2025 using Python (pandas, seaborn, matplotlib). Explores how GDP, health, freedom, generosity, and corruption perception influence global happiness.
World Happiness Data Visualization_Aarhus University
A Python Flask app representing world happiness from 2015-2017 using D3.js - Plotly.js and AnyChart.js to create visualization.
Final project for CS360 (Machine Learning) where I use linear regression and K Neighbors Regressor to predict a country's happiness score
Stepwise regression and factor analysis on world happiness data using SPSS
Introduction to Data Science (STA 230) Project
Analysis of World Happiness Report from 2005-2021.
A data science project to perform Data Visualization on World Happiness Index 2020.
Working with World Happiness Data on Python
PySpark, MongoDB Assignments
Analyze World Happiness Report data for 168 countries and generate machine learning forecasts through 2030 using Python, PyTorch, and scikit-learn.
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