MLOps Prototyping
CommunityDesign reproducible ML prototyping notebooks.
Authorfmind
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill guides data scientists to build standardized, reproducible Jupyter notebooks for MLOps prototyping, emphasizing configuration management and pipeline integrity.
Core Features & Use Cases
- Structured notebook layout: Imports -> Configs -> Load -> EDA -> Modeling -> Eval
- Robust configuration management: global constants, seeds, and explicit paths to prevent leakage
- Transition to production: guidance to move stable blocks into a Python package and automate reproducibility checks
Quick Start
Create a new notebook following the standard structure (Imports -> Configs -> Load -> EDA -> Modeling -> Eval) and initialize a reproducibility-friendly environment using a clean virtual environment.
Dependency Matrix
Required Modules
None requiredComponents
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: MLOps Prototyping Download link: https://github.com/fmind/mlops-python-package/archive/main.zip#mlops-prototyping Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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