Build production-grade machine learning pipelines with ease. This skill gives you ready-to-use code templates and expert guidance. You can set up MLflow for experiment tracking and Kubeflow for pipeline orchestration.
Data scientists and MLOps engineers can automate model training and validation. The skill covers feature stores with Feast, model registries, and hyperparameter tuning. It helps you avoid common pitfalls and save time.
Global
mkdir -p ~/.claude/skills/ml-pipelineProject
mkdir -p .claude/skills/ml-pipelineSource Repository
Explore Runlllllllama/rigorpilot-skills
Plan and rank quick deep learning exploration runs with clear boundaries
Run Trainlllllllama/rigorpilot-skills
Run deep learning training conservatively with structured logs and metrics
Env And Assets Bootstraplllllllama/rigorpilot-skills
Safe and careful setup of conda environments and asset paths for deep learning reproduction
Env And Assets Bootstraplllllllama/ai-paper-reproduction-skill
Prepare conda-first environment and asset paths for deep learning reproduction
Data Visualizationanthropics/knowledge-work-plugins
Pick the right chart, write clean Python code, and design for everyone
Powerbi Modelinggithub/awesome-copilot
Expert guidance for building optimized Power BI semantic models with star schemas and DAX
Power Bi Dax Optimizationgithub/awesome-copilot
Make your Power BI DAX formulas faster and easier to maintain
Bigquery Basicsgoogle/skills
Easily analyze massive datasets with SQL and built-in machine learning