How to get started

We assume basic familiarity with scikit-learn. If you haven’t worked with scikit-learn before, check out their getting-started guide.

We have a number of tutorial notebooks. If you like to run them interactively, you can launch them on Binder without having to install anything.

• Forecasting with sktime
• Univariate time series classification with sktime
• Multivariate time series classification with sktime
• Benchmarking with sktime
• Feature extraction with tsfresh transformer
• Shapelets and the Shapelet Transform with sktime
• Time series classification with Mr-SEQL
• Demo of ROCKET transform
• Demo of the PlateauFinder transformer
• Loading data in sktime

The notebook files can be found here.