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A library making it very easy to produce forecasts using a wide range of models, from ARIMA to deep learning. Also does ensembling, model selection and more.
A python library for time series forecasting and analysis with temporal data structure always in mind. Includes a variety of predictive models with unified interface along with EDA and validation methods
Provides methods to find change points in time series such as shifts in the mean or scale of the signal as well as more complex changes in the probability distribution or frequency.
A scikit-learn compatible library for learning with time series/panel data including time series classification/regression and (supervised/panel) forecasting
Library for creating time-series-forecasting-as-a-service platforms/websites, with a fully automated data ingestion, pre-processing, prediction and results visualization pipeline.
Python implementation of the winning forecasting method of the M4 competition combining exponential smoothing with a recurrent neural network using PyTorch
Labelled 1D and 2D data container for storing type-heterogeneous tabular data of any type, including time series, and encapsulates feature extraction and transformation modelling in an sklearn-compatible transformer interface, work in progress.