A data scientist can use this skill to design and analyze controlled experiments. It covers A/B testing, sample sizes, and statistical checks like the Bonferroni correction. You can also build predictive models with tools like Scikit-learn and XGBoost. The skill helps turn numbers into clear business decisions.
This skill includes feature engineering pipelines and model evaluation with cross-validation. It uses Python, R, and SQL. Whether you are analyzing causal effects or building classification models, this skill provides the code and steps you need.
Global
mkdir -p ~/.claude/skills/senior-data-scientistProject
mkdir -p .claude/skills/senior-data-scientistSource 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