AI & Machine Learning
TimesFM Forecasting
Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Automatically checks system RAM/GPU before loading the model, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model. For classical statistical time series models (ARIMA, SARIMAX, VAR) use statsmodels; for time series classification/clustering use aeon.
- Publisher / source
- foryourhealth111-pixel/Vibe-Skills (found on GitHub top repositories)
- Upstream record
- foryourhealth111-pixel/Vibe-Skills
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
718f09ac79687b237bc0d9e04afdc8f63782a04d866cab6313772b1b13de448d