A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
-
Updated
Mar 19, 2023
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
The easiest way to orchestrate and observe your data pipelines
A curated list of articles that cover the software engineering best practices for building machine learning applications.
An open-source ML pipeline development platform
Fire up your models with the flame
A Collection of GitHub Actions That Facilitate MLOps
Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.
A pipeline to CI/CD of a machine learning model on Google Cloud Run
Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]
Efficient streaming data ingestion, transformation & activation
A ready to use architecture for processing data and performing machine learning in Azure
Repo for running Whylogs as part of a CI workflow using github actions.
Demo usage of Weights & Biases for ML Ops
Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring
Raccogliamo qui tutti i link alle risorse menzionate durante i nostri QShare
A library of computer vision models and a streamlined framework for training them.
Data Science Experiments Repository of Ideas2IT
Sample Airflow ML Pipelines
interactive coding environment for microservices demo
Add a description, image, and links to the ml-ops topic page so that developers can more easily learn about it.
To associate your repository with the ml-ops topic, visit your repo's landing page and select "manage topics."