ml-pipeline-workflow
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.
- Skills
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What it does and how to use it
A skill that teaches Claude Code to do general tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
- No commands to memorize: you talk in plain language and the skill does the rest.
Install (Claude Code)
mkdir -p .claude/skills/wshobson-agents__ml-pipeline-workflow && curl -fsSL https://doutorai.pt/data/lib/skills__wshobson-agents__ml-pipeline-workflow.md -o .claude/skills/wshobson-agents__ml-pipeline-workflow/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
---
name: ml-pipeline-workflow
description: 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.
---
# ML Pipeline Workflow
Complete end-to-end MLOps pipeline orchestration from data preparation through model deployment.
## Overview
This skill provides comprehensive guidance for building production ML pipelines that handle the full lifecycle: data ingestion → preparation → training → validation → deployment → m
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