ml-pipeline-workflow
Description
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment.
How to Use
- Visit the GitHub repository to get the SKILL.md file
- Copy the file to your project root or .cursor/rules directory
- Restart your AI assistant or editor to apply the new skill
Full Skill Documentation
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.
Tags
Related Skills
langchain-architecture
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns.
data-storytelling
Transform data into compelling narratives using visualization, context, and persuasive structure.
pyhealth
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, ND
biomni
Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GW
scientific-schematics
Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological p