ml-ops

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

Efficient streaming data ingestion, transformation & activation

Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]

A ready to use architecture for processing data and performing machine learning in Azure

Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring

Vehicle data classification (supervised, unsupervised learning)

Repo for running Whylogs as part of a CI workflow using github actions.

Demo usage of Weights & Biases for ML Ops

Raccogliamo qui tutti i link alle risorse menzionate durante i nostri QShare

A prefect extension that builds on top of the task decorator to reduce negative engineering!

A library of computer vision models and a streamlined framework for training them.

Data Science Experiments Repository of Ideas2IT

Sample Airflow ML Pipelines