dmatrix / ray-core-tutorialLinks
Introduction to Ray Core Design Patterns and APIs.
☆71Updated last year
Alternatives and similar repositories for ray-core-tutorial
Users that are interested in ray-core-tutorial are comparing it to the libraries listed below
Sorting:
- Serverless Python with Ray☆58Updated 2 years ago
- Scaling Python Machine Learning☆49Updated last year
- Distributed XGBoost on Ray☆149Updated last year
- ☆27Updated 2 years ago
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.☆37Updated 4 years ago
- 🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects☆82Updated 3 years ago
- A collection of Machine Learning examples to get started with deploying RAPIDS in the Cloud☆142Updated 9 months ago
- Notebooks for the O'Reilly book "Learning Ray"☆317Updated last year
- Chassis turns machine learning models into portable container images that can run just about anywhere.☆86Updated last year
- Supporting content (slides and exercises) for the Pearson video series covering best practices for developing scalable applications with …☆52Updated 7 months ago
- Kedro Plugin to support running workflows on Kubeflow Pipelines☆54Updated last month
- ☆58Updated last year
- Projects developed by Domino's R&D team☆78Updated 3 years ago
- Code samples for the Effective Data Science Infrastructure book☆115Updated 2 years ago
- Ray - A curated list of resources: https://github.com/ray-project/ray☆67Updated 2 months ago
- A repository that showcases how you can use ZenML with Git☆69Updated 3 weeks ago
- Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases wit…☆48Updated 3 years ago
- End to End example integrating MLFlow and Seldon Core☆52Updated 4 years ago
- Deep Learning how-to's using Lance file format☆19Updated 2 months ago
- An introductory tutorial about leveraging Ray core features for distributed patterns.☆78Updated last year
- A series of workshop modules introducing Feast feature store.☆19Updated 3 years ago
- This is suite of the hands-on training materials that shows how to scale CV, NLP, time-series forecasting workloads with Ray.☆427Updated last year
- Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.☆40Updated 7 months ago
- Joining the modern data stack with the modern ML stack☆199Updated 2 years ago
- Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow☆239Updated 2 years ago
- 🎲 A curated list of MLOps projects, tools and resources☆186Updated last year
- Machine Learning Projects with Flytekit☆37Updated 2 years ago
- Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).☆96Updated 2 years ago
- An efficient, to-the-point, and easy-to-use checklist to following when deploying an ML model into production.☆30Updated 2 years ago
- A series of Jupyter notebooks that walk you through Machine Learning with Apache Spark ecosystem using Spark MLlib, PyTorch and TensorFlo…☆82Updated last year