pytorch-forecasting
tslearn
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pytorch-forecasting | tslearn | |
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9 | 51 | |
3,533 | 2,761 | |
- | 1.8% | |
8.7 | 7.2 | |
8 days ago | 9 days ago | |
Python | Python | |
MIT License | BSD 2-clause "Simplified" License |
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pytorch-forecasting
- FLaNK Stack Weekly for 14 Aug 2023
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LSTM/CNN architectures for time series forecasting[Discussion]
Pytorch-forecasting
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[P] Beware of false (FB-)Prophets: Introducing the fastest implementation of auto ARIMA [ever].
To name a few: https://github.com/jdb78/pytorch-forecasting, https://github.com/unit8co/darts, https://github.com/Nixtla/neuralforecast
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A python library for easy manipulation and forecasting of time series.
Darts is a pretty nice one. I've recently been using pytorch-forecasting for larger models like the Temporal Fusion Transformer. https://github.com/jdb78/pytorch-forecasting
tslearn
We haven't tracked posts mentioning tslearn yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
darts - A python library for user-friendly forecasting and anomaly detection on time series.
sktime - A unified framework for machine learning with time series
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
Lime-For-Time - Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
snntorch - Deep and online learning with spiking neural networks in Python
Informer2020 - The GitHub repository for the paper "Informer" accepted by AAAI 2021.
nixtla - Python SDK for TimeGPT, a foundational time series model
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
uncertainty-baselines - High-quality implementations of standard and SOTA methods on a variety of tasks.