from scientific-agent-skills20,009
Comprehensive scikit-learn guidance for classification, regression, clustering, preprocessing, model evaluation, and production-ready ML pipelines.
Provides an end-to-end reference and runnable scripts for classical machine learning using scikit-learn. Covers supervised and unsupervised algorithms, preprocessing, model evaluation, hyperparameter tuning, and pipelines with practical examples and scripts for classification, clustering, and production workflows.
Use this skill when you need to build or evaluate classical ML models (classification/regression), compare algorithms, create reproducible pipelines, tune hyperparameters, or preprocess tabular/text data for modeling. It's suited for data exploration, model selection, and preparing models for production.
Best used by agents with Python execution and code-reading capabilities (Copilot-style or Claude Code / Codex-like agents), and any agent that can run prepared scripts and interpret outputs.
This skill has not been reviewed by our automated audit pipeline yet.
