A solution for creating balanced syndicate groups based on multiple criteria. The algorithm considers several important balancing factors. Balanced syndicate groups are strategically formed teams that maximize internal diversity while ensuring equitable distribution of characteristics across all groups. This approach creates teams with varied perspectives internally, yet maintains overall parity between different teams' collective attributes and capabilities.

The goal of this analysis is to develop a robust, data-driven approach to predict house prices in King County accurately. By leveraging machine learning techniques, we aim to create a model that can process the complex dataset, identify key price determinants, and provide reliable price estimates. This tool would be valuable for real estate professionals, potential buyers and sellers, and financial institutions in making informed decisions about property transactions and valuations.

What is the true significance of geopolitical risk in explaining movements in oil prices? Does Geopolitical Risk in the Middle East and North Africa have a stronger relationship with oil prices, than geopolitical risk in the non-Middle East and non-North Africa sectors of the world?

SpatioTemporal Autoregression of Renewable Energy Policy data

EV Customer Detection from Electricity Consumption

Analysis of risk factors for coronary heart disease.

The objective is to predict how many patients will visit the walk-in center each day in the next week. The center is open 7 day a week.

Statistical Analysis of Environmental Social Governance Scores by Enterprise State Ownership and Corruption Perceptions Index Rating