This is a solid reference skill for ML practitioners working across the stack. You get working examples for scikit-learn pipelines, PyTorch model training with proper evaluation loops, FastAPI deployment endpoints, and MLOps patterns. The code is production-minded with cross-validation, feature scaling, model serialization, and health checks built in. It covers the practical path from experimentation to serving models, though the MLflow section cuts off mid-implementation. Best when you need template code for common ML workflows rather than cutting-edge techniques. The examples assume you understand ML fundamentals and just need the boilerplate done right.
npx skills add https://github.com/personamanagmentlayer/pcl --skill ml-expert