Analyze datasets for statistical hypothesis testing and ML model validation.
npx skills add https://github.com/grasberg/sofia --skill data-scientist-grasberg
Please help me install this Agent Skill. Skill: data-scientist Source: https://github.com/grasberg/sofia/tree/main/workspace/skills/data-scientist Command: npx skills add https://github.com/grasberg/sofia --skill data-scientist-grasberg
Enable rigorous statistical analysis, ML model development, and experimental design to derive trustworthy insights from data.
Provide your dataset and ask for hypothesis testing, model comparison, and results visualization.
High-intent search queries and answers about installing and using this skill.
Hypothesis testing applies rigorous statistical inference to your dataset to validate assumptions. It requires Python-based tooling to execute the analysis, generate clear reports, and maintain guardrails against data leakage.
A/B test design uses power calculations and sequential testing guardrails to determine statistical significance. This ensures your experimental design yields trustworthy insights by preventing premature conclusions during data collection.
ML model validation evaluates pipelines and compares models using strict guardrails against data leakage. It applies Python-based tooling for feature engineering to ensure robust evaluation across diverse datasets.
Python-based tooling supports statistical analysis and ML pipelines across diverse datasets. It enables model comparison, feature engineering, and data visualization while maintaining strong validation standards.
Data visualization translates rigorous statistical analysis and ML model results into clear storytelling. It helps you communicate trustworthy insights to stakeholders by visualizing outcomes from your experimental design.
WynterJonesAnalyze datasets to produce statistical summaries and data-driven reports.
ScientiaCapitalExport fine-tuned models to GGUF and deploy with vLLM or Ollama.
DrugClawGenerate static and interactive scientific plots from research data using Python libraries.
chrishuffman5Modify machine learning training code and evaluate models in a keep/discard loop.
