flyteorg / flytelab
Machine Learning Projects with Flytekit
β35Updated last year
Alternatives and similar repositories for flytelab:
Users that are interested in flytelab are comparing it to the libraries listed below
- Flyte Documentation πβ77Updated last week
- Kedro Plugin to support running workflows on Kubeflow Pipelinesβ53Updated 5 months ago
- mlctl is the control plane for MLOps. It provides a CLI and a Python SDK for supporting key operations related to MLOps, such as "model tβ¦β25Updated 3 years ago
- Repository for makeinga a GitHub Actions for deploying to Kubeflow.β35Updated 3 years ago
- CookieCutter template for getting started with Flyte python projectsβ20Updated this week
- Projects developed by Domino's R&D teamβ76Updated 2 years ago
- demo CI/CD pipeline using MLRun, Kubeflow and GitHub Actionsβ50Updated 2 years ago
- Fine-tuning LLMs on Flyte and Union Cloudβ27Updated last year
- π Stream inferences of real-time ML models in production to any data lake (Experimental)β79Updated 2 years ago
- Scaling Python Machine Learningβ45Updated last year
- βοΈ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.β45Updated 5 months ago
- MLOps Python Libraryβ117Updated 2 years ago
- Concept drift monitoring for HA model servers.β101Updated last year
- End to End example integrating MLFlow and Seldon Coreβ51Updated 4 years ago
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.β37Updated 4 years ago
- A repository that showcases how you can use ZenML with Gitβ69Updated 6 months ago
- Convert monolithic Jupyter notebooks π into maintainable Ploomber pipelines. πβ78Updated 5 months ago
- real-time data + ML pipelineβ54Updated 3 weeks ago
- Specification of the IR for Flyte workflows and tasks. Also Interfaces for all backend services. https://docs.flyte.org/projects/flyteidlβ¦β28Updated last year
- Listens MLFlow model registry changes and deploy models based on configurationsβ21Updated last year
- MLflow-tracking server example with Minio and H2Oβ18Updated 5 years ago
- This repo is an approach to TDD in machine learning model operation. it covers project structure, testing essentials using pytest with Giβ¦β15Updated 4 years ago
- β23Updated last week
- Tools for MLflowβ36Updated last year
- Chassis turns machine learning models into portable container images that can run just about anywhere.β86Updated 9 months ago
- Orchestrate Spark Jobs from Kubeflow Pipelines and poll for the status.β52Updated 2 years ago
- β54Updated last year
- A set of IaC artifacts to automatically configure the infrastructure resources needed by a Flyte deploymentβ25Updated last week
- MLFlow Deployment Plugin for Ray Serveβ43Updated 2 years ago
- Machine Learning Inference Graph Specβ21Updated 5 years ago