flow-forecast

Why we included this project

Flow Forecast gives teams a complete deep learning toolkit for time series work, so you do not have to stitch together notebooks from several model repositories. It packages modern architectures, including transformers, attention models, GRUs, and ODE-based approaches, behind a single PyTorch API, and it ships with interpretability metrics and model serving built in. The project started as flood and river flow forecasting, which explains its practical focus on real forecasting problems, but the same tooling handles demand, energy, or sensor prediction. Data scientists and ML engineers who want to compare modern models quickly, or run anomaly detection alongside forecasting, get a coherent alternative to juggling many single-purpose libraries.