Does it handle different expertise levels?

Yes, the skill explicitly gathers your current proficiency level—from beginner to expert—to tailor the depth, complexity, and type of resources recommended.

What kind of output does the Deep Learning Scholar provide?

It generates a structured directory containing a modern HTML learning guide, a resources.json for data portability, a knowledge graph, and a Markdown summary.

How does this skill gather learning materials?

It uses advanced search strategies across global authoritative sources like GitHub, arXiv, O'Reilly, and top-tier university course sites to find the most relevant and high-quality materials.

Can it download academic papers automatically?

Yes, it prioritizes downloading PDFs from open-access repositories like arXiv and ACL Anthology, automatically renaming them to a standard format for better organization.

Deep Learning Scholar

Name: Deep Learning Scholar
Author: zjfls

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데이터 과학 및 ML

Automates the collection of authoritative deep learning resources and generates structured, multi-stage learning paths with interactive HTML guides.

소개

Deep Learning Scholar is a specialized Claude Code skill designed to help developers and researchers systematically master complex technical domains. By gathering high-quality books, tutorials, frameworks, and academic papers from global sources, it builds a comprehensive knowledge graph tailored to the user's expertise level. The skill not only identifies the best resources but also automates paper downloads from repositories like arXiv, extracts key concepts, and produces an interactive, dark-themed HTML learning dashboard to track progress and visualize the curriculum from beginner to expert levels.

주요 기능

Structural analysis of technical concepts to create logical learning dependencies
Automated collection of authoritative books, blogs, and tutorials from global sources
Standardized file organization for research papers and structured resource data
1 GitHub stars
Generation of a modern, dark-themed interactive HTML learning guide with progress tracking
High-priority paper downloading and standardized renaming from arXiv and Semantic Scholar

사용 사례

Building a systematic curriculum for new AI sub-fields like Transformers or Reinforcement Learning
Onboarding developers to specific deep learning frameworks with tailored, level-appropriate resource lists
Creating an organized bibliography and knowledge base for a professional research project

소개

주요 기능

Structural analysis of technical concepts to create logical learning dependencies
Automated collection of authoritative books, blogs, and tutorials from global sources
Standardized file organization for research papers and structured resource data
1 GitHub stars
Generation of a modern, dark-themed interactive HTML learning guide with progress tracking
High-priority paper downloading and standardized renaming from arXiv and Semantic Scholar

사용 사례

Building a systematic curriculum for new AI sub-fields like Transformers or Reinforcement Learning
Onboarding developers to specific deep learning frameworks with tailored, level-appropriate resource lists
Creating an organized bibliography and knowledge base for a professional research project