Ml Pipeline
Helps with machine learning, pipeline automation as part of automating DevOps pipelines and CI/CD workflows workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add ml-pipeline npx -- -y @trustedskills/ml-pipeline
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"ml-pipeline": {
"command": "npx",
"args": [
"-y",
"@trustedskills/ml-pipeline"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill automates and orchestrates machine learning pipelines. It allows users to define a series of steps, such as data preprocessing, model training, evaluation, and deployment, which are then executed in a predefined order. The goal is to streamline the ML development process and reduce manual effort.
When to use it
- Automating repetitive tasks in your machine learning workflow.
- Deploying new models or updating existing ones with minimal intervention.
- Ensuring consistent execution of ML experiments across different environments.
- Managing complex ML projects involving multiple data sources and model versions.
Key capabilities
- Pipeline definition via configuration files.
- Automated task scheduling and dependency management.
- Model training and evaluation.
- Deployment to various platforms.
Example prompts
- "Run the 'model_training' pipeline."
- "Deploy the latest model version to production."
- "Show me the status of the data preprocessing step in the 'feature_engineering' pipeline."
Tips & gotchas
The skill requires familiarity with machine learning concepts and pipeline architecture. Ensure that all dependencies are correctly configured before running a pipeline.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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