Reverse Dependencies of tsfresh

The following projects have a declared dependency on tsfresh:

• astroCAST — Package to analyze calcium fluorescence events in astrocytes
• ballet — Core functionality for lightweight, collaborative data science projects
• bigdl-chronos — Scalable time series analysis using AutoML
• bigdl-chronos-spark2 — Scalable time series analysis using AutoML
• bigdl-chronos-spark3 — Scalable time series analysis using AutoML
• bletl — Package for parsing and transforming BioLector raw data.
• chronos_ai — no summary
• datasetsDynamic — A package to load datasets for benchmarking prescriptive analytics approaches dynamically
• dsu — no summary
• EgC-Package — A small example package from EGC
• egc2delete — A small example package from EGC
• enigmx — enigmx package
• etna — ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun.
• featuretools-tsfresh-primitives — TSFresh primitives for featuretools
• flarespy — Find flares in TESS light curves
• forecastga — A Python tool to forecast GA data using several popular timeseries models
• functime — Time-series machine learning at scale.
• mdata — no summary
• metats — Meta-Learning for Time Series Forecasting
• mlcf — MLCF - Machine Learning Toolkit for Cryptocurrency Forecasting
• moosir-feature — Add a short description here!
• mPowerGait — python package wrapper for mpower data pipeline
• pada — a ligthweight feature manage framework
• pylife — General Fatigue library
• raptor-functions — no summary
• raymics — Raymics Tools
• rfwtools — A package for working with CEBAF's C100 RF harvester waveforms
• sciope — The sciope toolbox for surrogate modeling, likelihood-free parameter inference and black-box optimization.
• sktime — A unified Python toolbox for machine learning with time series
• sybil-scorer — A sybil scoring tool
• ts-train — Time-Series Handling for Machine Learning Tasks
• tsad — Time Series Analysis for Simulation of Technological Processes
• tsai — Practical Deep Learning for Time Series / Sequential Data library based on fastai & Pytorch
• TSInterpret — todo
• vus — Volume Under the Surface