scikit-learn

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

Install

KitScout test notes

Not tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.

Similar tools

• rea-tool-design 456,653 ★
  Audit, investigate, design, or change REA investigation tools, CLI/MCP contracts, provider capabilities, and E
• code-review 323,485 ★
  Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does th
• codebase-design 323,485 ★
  Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interfac
• domain-modeling 323,485 ★
  Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLO
• implement 323,485 ★
  Implement a piece of work based on a spec or set of tickets.