Franz Kiraly

Forecasting is evolving rapidly, with deep learning, foundation models, and agentic AI opening up new possibilities while making it increasingly difficult to compare methods fairly and identify the right approach for a given application. This hands-on workshop provides a practical introduction...

sktime is a widely used scikit-learn compatible library for learning with time series. sktime is easily extensible by anyone, and interoperable with the pydata/numfocus stack.

Explore tsbootstrap and sktime in our 4-hour tutorial, focusing on enhancing time series forecasting and analysis. Discover how tsbootstrap's bootstrapping methods improve uncertainty quantification in time series data, integrating with sktime's forecasting models.

sktime is a widely used scikit-learn compatible library for learning with time series. sktime is easily extensible by anyone, and interoperable with the pydata/numfocus stack.

The forecasting module of sktime provides a unified, sklearn-compatible, and composable interface. This tutorial covers advanced topics in forecasting using sktime: probabilistic forecasting, and forecasting with panel data, including global/hierarchical forecasting.