End-to-End Forecasting with TimesFM 2.5: Backtesting, Covariates, Anomaly Detection, and Scalable Colab Deployment

Google has released an updated workflow for TimesFM 2.5, a time-series forecasting model designed for retail data analysis. This release introduces support for backtesting, external covariates, and anomaly detection to improve predictive accuracy in complex environments. These additions provide developers with more robust tools for scaling time-series tasks directly within Colab environments.