Rules

9 rules available in the Claude directory

Creative prompt for fine-tuning, evaluating, and deploying optimized embedding models using Jina AI tools.

Creative prompt for designing scalable, automated ML pipelines from experimentation to production deployment.

Comprehensive system prompt for developing production-ready data science pipelines, models, and analyses using best practices.

Creative prompt for building fair, secure, and scalable ML pipelines with emphasis on ethics, monitoring, and production readiness.

Engineer production ML pipelines with PyTorch, MLflow, and Kubeflow, using Claude's reasoning for hyperparameter tuning and model serving.

Comprehensive guide for building reproducible ML pipelines with scikit-learn, PyTorch, and MLOps tools in Claude Code.

Design production ML workflows with PyTorch, MLflow, Ray for scalable training and serving.

Expert prompt for deploying production ML pipelines in Python with MLflow, Scikit-learn, and Ray, using Claude's tools for experiment tracking.

Production ML pipelines with PyTorch, MLflow, and Kubeflow for scalable model deployment.