mcaf-ml-ai-delivery
OfficialDeliver ML/AI projects with confidence.
Software Engineering#project management#mlops#data science#experimentation#responsible ai#ai delivery
Authormanagedcode
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides structured guidance and workflows for the successful delivery of Machine Learning and Artificial Intelligence projects, ensuring all aspects from data to responsible AI are covered.
Core Features & Use Cases
- End-to-End Project Guidance: Covers the entire ML/AI project lifecycle, including framing, data exploration, experimentation, testing, responsible AI, and operations.
- Structured Workflows: Implements a "Ralph Loop" for iterative planning, execution, and review, ensuring concrete deliverables and verifiable outcomes.
- Use Case: When starting a new ML project to predict customer churn, use this Skill to define the project scope, plan data exploration, set up experimentation, and ensure responsible AI principles are integrated from the outset.
Quick Start
Use the mcaf-ml-ai-delivery skill to define the delivery workflow for a new ML feature.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: mcaf-ml-ai-delivery Download link: https://github.com/managedcode/MCPGateway/archive/main.zip#mcaf-ml-ai-delivery Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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