Library/tslearn
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tslearn-team/tslearn

tslearn

The machine learning toolkit for time series analysis in Python

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tslearn-team

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Created

May 4, 2017

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README Summary

tslearn is a Python package that provides machine learning tools dedicated to time-series analysis. It offers implementations of algorithms for time series clustering, classification, and regression, with a focus on Dynamic Time Warping (DTW) and other time series-specific distance measures. The package is designed to be compatible with scikit-learn and provides specialized tools for handling variable-length time series data.

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Time Series AnalysisDynamic Time WarpingTime Series ClusteringTime Series ClassificationSequential Data MiningTemporal Pattern RecognitionDistance Metric LearningTime Series PreprocessingBarycenter ComputationSoft-DTW Alignment

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Time Series AnalysisDynamic Time WarpingTime Series ClusteringTime Series ClassificationSequential Data MiningTemporal Pattern RecognitionDistance Metric LearningTime Series PreprocessingBarycenter ComputationSoft-DTW AlignmentTime SeriesCloud ComputingTemporal Pattern ClassificationTelecommunicationsTime Series Similarity SearchTemporal DataFinanceSeasonal Pattern AnalysisClassical ML for Time SeriesSpecialized Domain LibrariesAnomaly Detection in Sequential DataJupyter NotebooksSequence Alignment and MatchingSequential DataSupply ChainResearch EnvironmentsTime Series Forecasting Feature EngineeringSelf-hostedHealthcareEnergyTrend DetectionIoTManufacturingPython

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Updated 25 days ago

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Python100.0%

Timeline

Project created
May 4, 2017
Forked
Mar 22, 2026
Your last push
25 days ago
Upstream last push
11 days ago
Tracked since
Mar 19, 2026

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