skforecast
A Python library for time series forecasting using scikit-learn compatible machine learning models.
What is skforecast?
Skforecast is a Python library for time series forecasting using machine learning models. It provides a scikit-learn compatible API that allows data scientists and developers to build, validate, and deploy forecasting models with popular estimators like LightGBM, XGBoost, and CatBoost. The library simplifies the entire forecasting workflow, from feature engineering to production deployment.
Data scientists, machine learning engineers, and analysts who need to build and deploy time series forecasting models using Python and scikit-learn compatible tools.
Developers choose Skforecast for its seamless integration with the scikit-learn ecosystem, comprehensive forecasting capabilities, and production-ready tooling that simplifies the entire model development lifecycle.
Overview
Time series forecasting with machine learning models
Use Cases
Best For
- Building time series forecasting models with scikit-learn compatible estimators
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