experiment-tracking
CommunityReproducible ML experiments tracked end-to-end.
Authorpluginagentmarketplace
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill consolidates and standardizes the tracking of ML experiments to ensure reproducibility across teams and platforms, reducing drift and enabling reliable comparisons.
Core Features & Use Cases
- Experiment logging: Log parameters, metrics, artifacts, and environment metadata across MLflow, Weights & Biases, Neptune, and model registries.
- Model registry integration: Versioned models with promotion and deployment tracking.
- Collaboration & auditability: Compare runs, share dashboards, and maintain reproducible experiment histories.
Quick Start
Example setup: configure a tracking URI and log a simple run using MLflow, WANDB, or Neptune from a Python script.
Dependency Matrix
Required Modules
pyyaml
Components
scriptsreferencesassets
💻 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: experiment-tracking Download link: https://github.com/pluginagentmarketplace/custom-plugin-mlops/archive/main.zip#experiment-tracking Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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