From jeremylongshore-claude-code-plugins-plus-skills
Executes wandb experiment logger operations for ML training, including experiment tracking, hyperparameter logging, and metric visualization.
How this skill is triggered — by the user, by Claude, or both
Slash command
/jeremylongshore-claude-code-plugins-plus-skills:wandb-experiment-loggerThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides automated assistance for wandb experiment logger tasks within the ML Training domain.
This skill provides automated assistance for wandb experiment logger tasks within the ML Training domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with wandb experiment logger" Result: Provides step-by-step guidance and generates appropriate configurations
| Error | Cause | Solution |
|---|---|---|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |
Part of the ML Training skill category. Tags: ml, training, pytorch, tensorflow, sklearn
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin ejentum-reasoningSets up ML experiment tracking with MLflow or Weights & Biases, configuring environment and generating code for logging parameters, metrics, and artifacts.
Guides ML experiment logging, versioning, and reproducibility using MLflow, Weights & Biases, DVC for tracking params, metrics, models, and artifacts in Python projects.
Logs ML training metrics via Python API, fires structured alerts for diagnostics, and retrieves/analyzes logged metrics via CLI. Syncs to Hugging Face Spaces for real-time dashboards.