Comprehensive exploration of the Bike Sharing Problem using advanced Machine Learning for demand forecasting and Mathematical Linear Optimization for strategic bike allocation. Includes detailed Jupyter notebooks covering model development, analysis, and optimization solutions.

Python implementation of a toolkit for researchers studying electoral polarization. Features ideological and affective polarization analysis, issue salience modeling, and comprehensive statistical validation following Ginzburg's (2024) framework. Jupyter Notebook based.