machine-learning-ops
v1.2.2ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
by Seth HobsonMIT38.6kupdated 4 days ago
Source
git clone https://github.com/wshobson/agentsClone the source, then follow the repository's marketplace instructions for your runtime. The plugin root is plugins/machine-learning-ops/ inside the repository.
Layout
├── .codex-plugin/plugin.json├── .claude-plugin/plugin.json├── skills/ml-pipeline-workflow/SKILL.md└── skills/recsys-pipeline-architect/SKILL.md
Skills2
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced X For You algorithm. Use when building any system that picks "the top K items for a (user, context)" — content feeds, search ranking, RAG rerankers, task prioritizers, notification triage, ad selection.
Manifests2
{
"name": "machine-learning-ops",
"version": "1.2.2",
"description": "ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows",
"skills": "./skills/",
"author": {
"name": "Seth Hobson",
"email": "seth@major7apps.com"
},
"license": "MIT",
"interface": {
"displayName": "Machine Learning Ops",
"shortDescription": "ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps…",
"category": "Coding"
}
}{
"name": "machine-learning-ops",
"version": "1.2.2",
"description": "ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows",
"author": {
"name": "Seth Hobson",
"email": "seth@major7apps.com"
},
"license": "MIT"
}