sktime - A Unified Toolbox for ML with Time Series

This tutorial is about sktime - a unified framework for machine learning with time series. sktime features various time series algorithms and modular tools for pipelining, ensembling and tuning. You will learn how to use, combine and evaluate different algorithms on real-world data sets and integrate functionality from many existing libraries, including scikit-learn. Description Time series are ubiquitous in real-world applications, but often add considerable complications to data science workflows. Many machine learning libraries (e.g. scikit-learn) focus on non-temporal data. And even though there are many time series libraries, they are often incompatible with each other. In this tutorial, we will present sktime - a unified framework for machine learning with time series (). sktime covers multiple time series learning problems, including time series transformation, classification and forecasting, among others. In addition, sktime allows you to easily
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