post-modern-stack
domino-research
| post-modern-stack | domino-research | |
|---|---|---|
| 2 | 3 | |
| 181 | 76 | |
| - | - | |
| 2.2 | 0.0 | |
| 12 months ago | about 2 years ago | |
| Python | Python | |
| MIT License | 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.
post-modern-stack
-
[Advice] MLOps Course recommendations
End-to-end stuff, full-fledge stacks: https://github.com/jacopotagliabue/post-modern-stack
-
Small to Reasonable Scale MLOps - An Approach to Effective and Scalable MLOps when you're not a Giant like Google
Post Modern Stack
domino-research
-
[N] Open Sourcing Checkpoint 🛂
Here is a direct URL: https://github.com/dominodatalab/domino-research/tree/main/checkpoint
-
Open-sourcing Bridge 🎉
The Domino R&D team is open-sourcing Bridge, a tool that turns your model registry into the declarative source-of-truth for model deployment and hosting.
-
[Discussion] Look for service to upload a model and receive a REST API endpoint, for serving predictions
(Disclosure, I am a maintainer on this project) You should checkout Bridge - it deploys models directly from an MLflow registry to SageMaker inference endpoints (hosted APIs). It basically turns your registry into a declarative source of truth for your hosting. The advantage of this approach is that it provides a clean way to update/upgrade your APIs from the same place you're tracking your new versions, experiments etc. One source of truth. You can get an MLflow registry up in a couple minutes if you don't have one.
What are some alternatives?
MLSys-NYU-2022 - Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
huggingface_hub - The official Python client for the Huggingface Hub.
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]