From jeremylongshore-claude-code-plugins-plus-skills
Configures MLflow tracking setup for ML training workflows. Generates code, configurations, and best practices for experiment tracking with PyTorch, TensorFlow, scikit-learn.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin langchain-py-packThis skill is limited to using the following tools:
This skill provides automated assistance for mlflow tracking setup tasks within the ML Training domain.
Sets up ML experiment tracking with MLflow or Weights & Biases: installs packages, initializes tools, and provides logging code for parameters, metrics, and artifacts.
Onboards users to MLflow by analyzing codebase for GenAI (LLMs, LangChain) or traditional ML (sklearn, PyTorch) use cases and guiding through quickstart tutorials and integrations.
Sets up MLflow tracking server, autologging for scikit-learn/PyTorch/TensorFlow/XGBoost, run comparisons with metrics/visuals, artifact management for reproducible ML workflows. For new projects, log migration, or CI/CD integration.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for mlflow tracking setup tasks within the ML Training domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with mlflow tracking setup" 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