Notebook Examples

Welcome to sktime’s notebook examples!

These consist of introductory notebooks, ordered by learning task.

For guided tutorials with videos, see our Tutorials page.

To run the notebooks interactively, you can launch them on binder without having to install anything.

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

Introduction

Introduction to sktime

Forecasting

Forecasting with sktime

Forecasting with sktime - appendix: forecasting, supervised regression, and pitfalls in confusing the two

Probabilistic Forecasting with sktime

Hierarchical, Panel and Global Forecasting with sktime

Time Series Classification, Regression, Clustering

Time Series Classification, Regression, Clustering & More

Transformations, pipelines

Transformers in sktime

Transformers cheat sheets

Forecasting Pipelines, Tuning, and AutoML

Changepoint, Anomaly or Outlier Detection

Anomaly, changepoint, and segment detection with sktime and skchange

Time Series Segmentation with sktime and ClaSP

Time series Distances, Kernels, Alignment

Overview of this notebook

Data formats and data sets

In-memory data representations and data loading

Benchmarking

Benchmarking with sktime

Benchmarking - comparing estimator performance