scalingpythonml / scaling-python-with-rayLinks
Serverless Python with Ray
☆59Updated 3 years ago
Alternatives and similar repositories for scaling-python-with-ray
Users that are interested in scaling-python-with-ray are comparing it to the libraries listed below
Sorting:
- Introduction to Ray Core Design Patterns and APIs.☆74Updated last year
- Scaling Python Machine Learning☆52Updated 2 years ago
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.☆37Updated 4 years ago
- An introductory tutorial about leveraging Ray core features for distributed patterns.☆79Updated 2 years ago
- Machine Learning Projects with Flytekit☆36Updated 2 years ago
- ☆59Updated 2 years ago
- Listens MLFlow model registry changes and deploy models based on configurations☆20Updated 2 years ago
- A repository that showcases how you can use ZenML with Git☆73Updated 4 months ago
- IbisML is a library for building scalable ML pipelines using Ibis.☆119Updated 5 months ago
- Distributed XGBoost on Ray☆152Updated last year
- Python library to run ML/data pipelines on stateless compute infrastructure (that may be ephemeral or serverless). Please see the documen…☆18Updated 2 years ago
- Kedro Plugin to support running workflows on Kubeflow Pipelines☆56Updated 6 months ago
- Chassis turns machine learning models into portable container images that can run just about anywhere.☆86Updated last year
- Unified Distributed Execution☆57Updated last year
- 🚀 Stream inferences of real-time ML models in production to any data lake (Experimental)☆81Updated 3 years ago
- Dataset registry DVC project☆85Updated last year
- Notebooks for the O'Reilly book "Learning Ray"☆341Updated last year
- ☆28Updated last month
- real-time data + ML pipeline☆53Updated last week
- A library to use `modal` as a backend for `joblib`.☆32Updated 11 months ago
- Convert monolithic Jupyter notebooks 📙 into maintainable Ploomber pipelines. 📊☆79Updated last year
- Ray-based Apache Beam runner☆42Updated 2 years ago
- Demo on how to use Prefect with Docker☆27Updated 3 years ago
- A work-in-progress book on Dask☆12Updated 2 years ago
- Generate beautiful, testable documentation with Jupyter Notebooks☆21Updated 3 years ago
- Documentation and resources for deploying JupyterHub on Hadoop☆19Updated 6 years ago
- Flyte Documentation 📖☆84Updated 9 months ago
- Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.☆40Updated 11 months ago
- An abstraction layer for parameter tuning☆35Updated 2 weeks ago
- Supporting content (slides and exercises) for the Pearson video series covering best practices for developing scalable applications with …☆53Updated 11 months ago