{"repo":"skforecast/skforecast","free":true,"listed":false,"github":"https://github.com/skforecast/skforecast","clone":"git clone https://github.com/skforecast/skforecast.git","description":"Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models","language":"Python","stars":1525,"topics":["forecasting","scikit-learn","machine-learning","python","data-science","exogenous-predictors","time-series","multi-series-forecasting","multi-step-forecasting","backtesting-forecasters"],"license":"BSD-3-Clause","category":"machine-learning","readme_excerpt":"--- --- Package AI assistant App Meta Testing Donation Community Affiliation Table of Contents - :information source: About The Project - :books: Documentation - :computer: Installation & Dependencies - :sparkles: What is new in skforecast? - :crystal ball: Forecasters - :mortar board: Examples and tutorials - :handshake: How to contribute - :memo: Citation - :money with wings: Donating - :scroll: License About The Project Skforecast is a Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models. It works with any estimator compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others. Why use skforecast? Skforecast simplifies time series forecasting with machine learning by providing: - :jigsaw: Seamless integration with any scikit-learn compatible estimator (e.g., LightGBM, XGBoost, CatBoost, etc.). - :repeat: Flexible workflows that allow for both single and multi-series forecasting. - :hammer and wrench: Comprehensive tools for feature engineering, model selection, hyperparameter tuning, and more. - :building construction: Production-ready models with interpretability and validation methods for backtesting and realistic performance evaluation. Whether you're building quick prototypes or deploying models in production, skforecast ensures a fast, reliable, and scalable experience. [!TIP] :sparkles: Try skforecast-ai , an AI forecasting assistant that ","default_branch":null,"files":null,"tree":[],"storefront":"/r/skforecast","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/skforecast/skforecast/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}