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Heidrich, Kiraly, & Ray - sktime - python toolbox for time series | PyData Global 2023
Discover SK-Time, a Python library for time series learning and forecasting, providing a toolbox for building, combining, and evaluating models with pre-processing, feature engineering, and visualization tools.
- SK-Time is a Python toolbox for time series learning and forecasting.
- It enables users to build and combine different forecasting models, including univariate and multivariate models.
- SK-Time supports pre-processing, feature engineering, and model selection, and provides a convenient interface for users to define their own forecasting models.
- The library also includes tools for benchmarking, grid search, and random search, making it easy to evaluate and compare different models.
- SK-Time is compatible with popular datasets and can be used with various backend parallelization libraries.
- The library is highly extensible and allows users to define their own forecasting models and preprocessors.
- SK-Time includes support for probabilistic forecasting, including predicted intervals and quantiles.
- The library also includes tools for visualizing forecasting results, making it easy to understand and communicate the results of forecasting models.
- SK-Time is a flexible and extensible library that can be used for both research and industry applications.
- It provides a common interface for different forecasting models, making it easy to switch between models and compare results.
- The library includes support for multiple languages, including Python, R, and Julia.
- SK-Time is actively maintained and updated to keep up with the latest developments in the field of time series forecasting.
- The library is widely used in academia and industry, and has been applied to a wide range of applications, including finance, healthcare, and energy.