deep-learning-containers
gluonts
| deep-learning-containers | gluonts | |
|---|---|---|
| 1 | 4 | |
| 937 | 4,325 | |
| 1.3% | 2.7% | |
| 9.7 | 8.7 | |
| 6 days ago | 10 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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.
deep-learning-containers
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Deploying whisperX on AWS SageMaker as Asynchronous Endpoint
We are ready to create and deploy the sagemaker model on SageMaker as asynchronous endpoint using a image URI and the model data uploaded to S3. For different deployment regions and requirements, find suitable container images at AWS Deep Learning Container.
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.
pytorch-forecasting - Time series forecasting with PyTorch
tsai - Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
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.
sagemaker-python-sdk - A library for training and deploying machine learning models on Amazon SageMaker
chronos-forecasting - Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
datajob - Build and deploy a serverless data pipeline on AWS with no effort.
query-selector - LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
fold - 🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.