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deep-learning-engineer

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Turn research protocols into runnable ML code.

Software Engineering#training#pytorch#tensorflow#code-generation#ml#data-loading#machine-learning
AuthorSALTYf1SH
Version1.0.0
Installs0

System Documentation

What problem does it solve?

The machine learning engineer translates research protocols into runnable PyTorch or TensorFlow code, turning high-level experiments into executable training pipelines with data loading, model construction, and metric logging.

Core Features & Use Cases

  • Translates research protocols into concrete ML implementations in PyTorch or TensorFlow.
  • Bootstraps project structure with modular files (src/model.py, src/dataset.py, train.py) and reproducible defaults.
  • Supports end-to-end workflows from synthetic data testing to full training runs with metrics logging.

Quick Start

Provide a high-level protocol and let the toolkit generate a runnable PyTorch/TensorFlow training project with synthetic data.

Dependency Matrix

Required Modules

None required

Components

scripts

💻 Claude Code Installation

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Please help me install this Skill:
Name: deep-learning-engineer
Download link: https://github.com/SALTYf1SH/md-sci-skill/archive/main.zip#deep-learning-engineer

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