Shypd.aiThe largest open index of AI toolsskforecast is a Python library for time series forecasting that integrates with scikit-learn compatible models, statistical methods, and foundation models. It simplifies time series forecasting with machine learning, offering flexible workflows for single and multi-series predictions.
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skforecast is a Python library designed for time series forecasting, leveraging scikit-learn compatible models, statistical methods, and foundation models. It provides seamless integration with popular estimators like LightGBM, XGBoost, CatBoost, and Keras, allowing users to build robust forecasting solutions. The library supports flexible workflows for both single and multi-series forecasting, offering comprehensive tools for feature engineering, model selection, and hyperparameter tuning. It also includes production-ready models with interpretability and validation methods for backtesting and realistic performance evaluation. Whether for quick prototypes or production deployments, skforecast aims to deliver a fast, reliable, and scalable experience. Additionally, it offers Skforecast Studio, an interactive no-code application for visual model building that automatically generates production-ready Python code.
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