tslearn
sktime-dl
Our great sponsors
| tslearn | sktime-dl | |
|---|---|---|
| 51 | 1 | |
| 2,780 | 599 | |
| 1.4% | 0.0% | |
| 6.9 | 5.3 | |
| 6 days ago | 3 months ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tslearn
sktime-dl
What are some alternatives?
sktime - A unified framework for machine learning with time series
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification
pytorch-forecasting - Time series forecasting with PyTorch
tsai - Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
neural_prophet - NeuralProphet: A simple forecasting package
darts - A python library for user-friendly forecasting and anomaly detection on time series.
Time-series-classification-and-clustering-with-Reservoir-Computing - Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
scikit-hts - Hierarchical Time Series Forecasting with a familiar API
NeuralCDE - Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
R-Time-Series-Task-View-Supplement - R Time series packages not included in CRAN Task View: Time Series Analysis
hydra - HYDRA: Competing convolutional kernels for fast and accurate time series classification