mlops
CommunityMLOps: automate ML life cycles at scale.
Authorwilliamzujkowski
Version1.0.0
Installs0
System Documentation
What problem does it solve?
MLOps standardizes the end-to-end ML lifecycle from data to deployment, monitoring, and continuous improvement.
Core Features & Use Cases
- Experiment Tracking & Deployment: MLflow/Kubeflow/Kubeflow pipelines integration.
- Data & Feature Management: Feature stores, data/versioning, and reproducibility.
- Monitoring & Drift: Model performance monitoring and drift detection.
Quick Start
Set up an MLflow project or Kubeflow pipeline to train, evaluate, and deploy a model with drift monitoring.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: mlops Download link: https://github.com/williamzujkowski/standards/archive/main.zip#mlops Please download this .zip file, extract it, and install it in the .claude/skills/ directory.