model-lifecycle-manager
OfficialManage AI models from deployment to retirement.
Software Engineering#versioning#monitoring#drift detection#mlops#lifecycle#model management#retraining
AuthorEthical-AI-Syndicate
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the critical need for active management of AI/ML models in production, preventing performance degradation and ensuring reliable operation throughout their lifecycle.
Core Features & Use Cases
- Model Registration & Versioning: Tracks model versions, metadata, and lineage.
- Monitoring & Drift Detection: Sets up alerts for performance degradation and data/concept drift.
- Retraining & Rollback: Defines triggers and procedures for retraining and reverting to previous versions.
- Retirement Planning: Manages the process of deprecating and retiring models.
- Use Case: When a new machine learning model is deployed, this Skill ensures it's properly registered, monitored for drift, has a retraining strategy defined, and a rollback plan is in place.
Quick Start
Use the model-lifecycle-manager skill to set up monitoring and retraining for the newly deployed 'customer-churn-predictor' model.
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: model-lifecycle-manager Download link: https://github.com/Ethical-AI-Syndicate/skills/archive/main.zip#model-lifecycle-manager Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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