From jeremylongshore-claude-code-plugins-plus-skills
Manages hyperparameter tuning operations for ML training, providing guidance, code generation, and configs for data prep, model training, and experiment tracking. Triggers on 'hyperparameter tuner' phrases.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin framecraftThis skill is limited to using the following tools:
This skill provides automated assistance for hyperparameter tuner tasks within the ML Training domain.
Builds TensorFlow model trainers with guidance on data preparation, training, hyperparameter tuning, and experiment tracking. Activates on TensorFlow trainer phrases.
Optimizes ML model hyperparameters using grid, random, or Bayesian search via executed Python code with scikit-learn or Optuna. For tuning Random Forest, Gradient Boosting on datasets like Iris.
Autonomously runs deep learning experiments 24/7 in a THINK-EXECUTE-REFLECT loop with zero-cost GPU monitoring, Leader-Worker architecture, and constant-size memory.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for hyperparameter tuner tasks within the ML Training domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with hyperparameter tuner" 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