runhouse
gluonts
runhouse | gluonts | |
---|---|---|
6 | 4 | |
721 | 4,325 | |
3.7% | 2.7% | |
9.8 | 8.7 | |
4 days ago | 5 days ago | |
Python | 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.
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.
runhouse
- Runhouse
-
Better GPU Cluster Scheduling with Runhouse
With Runhouse, it’s easy to send code to your compute no matter where it lives, and efficiently utilize your resources across multiple callers scheduling jobs (e.g. researchers, pipelines, inference services, etc). We believe less is more when it comes to AI DevOps, so we don’t make any assumptions about the structure of your code or the infrastructure to which you’re sending it.
-
The Great MLOps Hoax: Is It Just Data Engineering in Disguise?
You may want to look at run.house [0] for a pretty powerful solution to many of these problems.
[0] https://github.com/run-house/runhouse
-
Who uses Apache Airflow for MLOps? Enlighten me.
I was the product lead for PyTorch and was seeing the same problem all over, so I've been working on a new tool for exactly this: https://github.com/run-house/runhouse
- Run-house/runhouse: Programmable remote compute and data across environments
-
How easy is it to migrate from one MLOps tool to another? And what SaaS platform would you recommend?
I've been working on a very flexible and low-lift OSS ML platform that sounds like it would suit your needs: https://github.com/run-house/runhouse
gluonts
-
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.
-
gluonts VS darts - a user suggested alternative
2 projects | 13 Apr 2023
-
[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`?
-
Cash-flow forecasting
-GluonTS
What are some alternatives?
omegaml - MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
darts - A python library for user-friendly forecasting and anomaly detection on time series.
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
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
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.