tsai
gluonts
tsai | gluonts | |
---|---|---|
4 | 4 | |
4,760 | 4,347 | |
3.6% | 3.2% | |
7.4 | 8.7 | |
30 days ago | 16 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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tsai
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Aeon: A unified framework for machine learning with time series
Also https://github.com/timeseriesAI/tsai
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What is the current state-of-art in sequence classification?
You might be interested in tsai. I am not affiliated with them and have not used tsai, but I have been planning to try it for too long … well :p
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[P] Deep Learning for time series forecasting (neuralforecast, python package)
how about tsai?
- Machine learning with Time series data
gluonts
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Show HN: Auto Wiki v2 – Turn your codebase into a Wiki now with diagrams
https://github.com/awslabs/gluonts is a great candidate for a sample wiki. It is an OSS lib, not great documentation, very hard to RTFM (unlike, say, sklearn which already has a great wiki), doubtful that awslabs would pay to produce.
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gluonts VS darts - a user suggested alternative
2 projects | 13 Apr 2023
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[Q] `py.typed` and `.typesafe`
I was looking at [`gluonts`](https://github.com/awslabs/gluonts/tree/dev/src/gluonts/core) source code and I found a `py.typed` file. That is something I always put in my type-annotated modules: it's literally an empty file which denotes that the module is marked for "internal or external use in type checking" [mypy docs](https://mypy.readthedocs.io/en/stable/installed_packages.html?highlight=py.typed#creating-pep-561-compatible-packages). However, I never saw before the `.typesafe` file. What does it denote? Does it have to be used alongside a `py.typed`?
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Cash-flow forecasting
-GluonTS
What are some alternatives?
darts - A python library for user-friendly forecasting and anomaly detection on time series.
sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
pytorch-forecasting - Time series forecasting with PyTorch
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
time-series-transformers-review - A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
nixtla - TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
sagemaker-python-sdk - A library for training and deploying machine learning models on Amazon SageMaker