This repository is a comprehensive, curated list of resources for deep learning, targeting researchers, students, and practitioners. It aims to provide a centralized hub for learning and staying updated on the rapidly evolving field of deep learning by aggregating books, courses, papers, frameworks, and datasets.

How It Works

The repository functions as a structured directory, meticulously organizing links and references across various categories. It leverages a community-driven approach, encouraging contributions to maintain its breadth and depth. The organization into distinct sections like Books, Courses, Papers, Frameworks, and Datasets allows users to navigate and discover relevant materials efficiently.

Quick Start & Requirements

This is a curated list, not a software package. No installation or execution is required. Users can directly browse the README for links to external resources.

Highlighted Details

• Extensive coverage of foundational and advanced deep learning topics.
• Includes a vast collection of academic papers, many with direct links to implementations.
• Lists numerous datasets crucial for training and benchmarking deep learning models.
• Provides an overview of popular deep learning frameworks and tools.

Maintenance & Community

The project is maintained by Christos Christofidis and relies on community contributions via pull requests.

Licensing & Compatibility

The content is licensed under a Creative Commons Zero (CC0) dedication, waiving all copyright and related rights. This allows for unrestricted use, modification, and distribution, including for commercial purposes.

Limitations & Caveats

As a curated list, the quality and maintenance of linked external resources are beyond the scope of this repository. Some links may become outdated over time.