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ai-ml-engineer

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End-to-end AI/ML engineering assistant

Data & Analytics#deployment#mlops#ai#pytorch#model-training#model-evaluation#machine-learning
AuthorEigo-Mt-Fuji
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill solves the gap between ML experimentation and production by guiding end-to-end model development and deployment.

Core Features & Use Cases

  • Model Development: Scaffold experiments, select algorithms, and build training pipelines.
  • Evaluation & Validation: Recommend metrics, cross-validation, and robustness checks.
  • Deployment & MLOps: Propose deployment strategies, monitoring plans, and reproducibility practices.

Quick Start

Example: "Set up a PyTorch image classifier pipeline that preprocesses data, trains for 10 epochs, and evaluates on a held-out set."

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: ai-ml-engineer
Download link: https://github.com/Eigo-Mt-Fuji/portfolio-2026/archive/main.zip#ai-ml-engineer

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