MLOps platforms and data pipelines
13 repos
Python-based tools and frameworks for orchestrating machine learning workflows, managing data pipelines, and tracking experiments in production environments. These systems handle end-to-end ML operations—from data ingestion and feature management through model training, deployment, and monitoring. Central projects like Feast (feature stores), ZenML, Flyte, and Aim provide different abstractions for reproducible ML infrastructure, while the cluster broadly covers data quality, experiment tracking, and workflow orchestration across the ML lifecycle.
Python · 10
Jupyter Notebook · 2
Scala · 1
data-science ·79,686
mlops ·77,761
data-quality ·68,475
data-engineering ·68,475
machine-learning ·68,092
deep-learning ·60,619
python ·57,271
pytorch ·55,064
llms ·49,962
distributed-training ·49,436
