Skill

data-science-workflow

Provides expert patterns for the end-to-end data science workflow and strategy based on Learning Data Science, Data Science at the Command Line, Data Science: The Hard Parts, and Data Science on AWS. Covers the lifecycle (ask/obtain/clean/explore/model/communicate) and OSEMN, Unix command-line data wrangling, data strategy and stakeholder communication, metrics design (funnels, stock-flow, P×Q), data leakage and drift, A/B testing, and MLOps lifecycle on AWS with SageMaker.

Bundled with Coacus. Its trust score, security findings and other files are on the plugin page.

npx [email protected] add dandgabr/Coacus