machine-learning-ops
πPluginwshobson/agents
|An MLOps plugin from the wshobson/agents ecosystem providing Claude Code with specialized agents and skills for ML pipeline management, model deployment, experiment tracking, and production monitoring.
Overview
Machine Learning Ops is a plugin from the wshobson/agents ecosystem, a comprehensive production-ready system of 73 focused, single-purpose plugins for Claude Code. This plugin provides specialized ML operations (MLOps) capabilities including model lifecycle management, training pipeline orchestration, model deployment, monitoring, and experiment tracking through dedicated AI agents and skills.
Key Features
- MLOps Agent Specialization: Provides dedicated agents for ML pipeline management, model training, deployment, and monitoring workflows
- Progressive Disclosure Skills: Includes specialized MLOps skills that load knowledge on demand, covering model versioning, feature stores, training pipelines, and production serving patterns
- Multi-Agent Orchestration: Integrates with the broader wshobson/agents workflow system, enabling complex ML workflows that coordinate across data engineering, infrastructure, and development plugins
- Three-Tier Model Strategy: Uses strategic model assignment (Opus for critical ML architecture decisions, Sonnet for complex tasks, Haiku for operational tasks) for optimal performance and cost
Who is this for?
- ML engineers who want AI-assisted guidance on building and managing production ML pipelines with Claude Code
- Data science teams looking for automated MLOps workflow orchestration including experiment tracking and model deployment
- Organizations adopting MLOps practices who need specialized AI support for model lifecycle management and infrastructure
Part of
wshobson-agents
Installation
/plugin marketplace add wshobson/agents/plugin install machine-learning-ops@claude-code-workflowsMore from this repository10
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