fyp-jupyter

功能与用途

Complete data science research workflow for Jupyter notebooks covering CRISP-DM methodology from data loading through model validation, with MLflow experiment tracking integration, phase-based workflow guidance (Exploration, Systematic Experimentation, Analysis, Documentation), and skill integration points. Use when working on FYP data science projects requiring systematic data preprocessing, EDA, feature engineering, modeling, statistical validation, experiment tracking, or needing guidance on what to work on at each project phase. Includes MLflow setup for tracking 30+ experiment runs, weekly work planning for 10-week FYP timeline, and clear decision framework for when to use which skill (fyp-jupyter, crossvit-covid19-fyp, fyp-statistical-validator, tar-umt-fyp-rds, tar-umt-academic-writing).

快速开始

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。