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crisp-dm-pipeline

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End-to-end CRISP-DM ML pipelines.

Data & Analytics#evaluation#reproducibility#data-science#machine-learning#ml-pipeline#crisp-dm
Authorjeverett32
Version1.0.0
Installs0

System Documentation

What problem does it solve?

CRISP-DM provides a structured, end-to-end approach to building machine learning solutions. This skill automates the entire workflow from problem framing to evaluation, producing either a notebook with clearly documented phases or a runnable Python project that can be deployed and scheduled.

Core Features & Use Cases

  • End-to-end CRISP-DM pipeline covering problem framing, data understanding, preparation, modeling, and evaluation.
  • Outputs a reusable artifact (notebook or Python project) with an optional operational layout for ETL, training, inference, and scheduling.
  • Suitable for both classification and regression tasks, with deterministic experiments and versioned artifacts.

Quick Start

Use this skill to generate your first CRISP-DM artifact (notebook or Python project) from your data and target variable.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: crisp-dm-pipeline
Download link: https://github.com/jeverett32/INTEX_2026_SKILLS/archive/main.zip#crisp-dm-pipeline

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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