Scientific Prediction & Simulation
Purpose
Predict scientific outcomes, material properties, and time series using computational models and simulation.
Key Datasets
- Materials Project (materials-toolkits/materials-project): 133K+ materials with DFT-computed properties (band gap, formation energy, elastic moduli, etc.)
- FRED (fred.stlouisfed.org): Federal Reserve Economic Data — macroeconomic time series (GDP, CPI, unemployment, interest rates)
Protocol
- Problem formulation — Define target variable, features, and prediction horizon
- Data preparation — Feature engineering, normalization, train/test split
- Model selection — Choose appropriate model class (regression, time series, ML, physics-informed)
- Training & validation — Fit model, cross-validate, tune hyperparameters