Understanding Complexity Through Mathematics
Pattern exists to make advanced quantitative thinking accessible through real-world systems.
The platform investigates how mathematics explains markets, music, biology, performance, and decision-making.
Core Disciplines
- Applied Mathematics
- Data Science
- Signal Processing
- Optimization
- Statistical Modeling
- Machine Learning
Domains
Finance
Markets, earnings, portfolio theory, prediction, risk.
Music
Signal processing, acoustics, Fourier analysis, harmonic structure.
Basketball
Shot optimization, efficiency, lineup analysis, game theory.
Biology
Tumor growth modeling, population dynamics, genetics, epidemiology.
Decision Science
Behavioral economics, probability, forecasting, optimization.
Methodology
All datasets used on Pattern are:
- From legitimate public sources (government databases, universities, public APIs)
- Properly attributed with source URLs
- Licensed for public use (Public Domain, Creative Commons, ODbL)
- Validated for quality and completeness
- Updated automatically through ETL pipelines