GitHub repository: BegisM/Contribution-to-Climate-Change-Research
Primary language: Jupyter Notebook
Description: This project analyzes temperature data from 10 cities (1900-2000) to study global warming trends. It uses Linear Regression, Polynomial Regression, and Support Vector Regression (SVR) to model the data. Ensemble methods like stacking, weighted averaging, and Gradient Boosting are applied for improved predictions.