Project Title

pwc — A Repository for Machine Learning Papers with Code

Overview

The 'pwc' GitHub repository is a curated collection of machine learning papers with corresponding code implementations. It is designed to provide researchers and developers with a comprehensive resource for the latest advancements in the field. The project is unique in its focus on maintaining a weekly updated list of papers and code, sorted by stars, making it an invaluable tool for staying current in the rapidly evolving landscape of machine learning.

Key Features

Curated list of machine learning papers with code
Weekly updates to keep the repository current
Sorted by stars for easy identification of popular and impactful work

Use Cases

Researchers looking for the latest machine learning papers and their implementations
Developers seeking to integrate cutting-edge algorithms into their projects
Educators needing up-to-date resources for teaching advanced machine learning concepts

Advantages

Provides a single, easily navigable source for both papers and code
Weekly updates ensure the content remains relevant and current
Sorted by stars, allowing users to quickly find the most popular and influential work

Limitations / Considerations

The repository is no longer actively maintained, which may limit the inclusion of the most recent papers and code
The reliance on community contributions for updates and additions may result in some gaps in coverage
The project's focus on stars as a sorting mechanism may not always reflect the quality or relevance of the work

arXiv: A repository of electronic preprints (known as e-prints) approved for publication after moderation, but also includes papers, which are not peer-reviewed. It differs from 'pwc' in that it is not specifically focused on machine learning and does not provide code implementations.
Papers with Code: A resource that provides access to state-of-the-art machine learning papers and their associated code. It differs from 'pwc' in its more interactive and comprehensive approach, offering benchmarks and comparisons across different papers and models.

Basic Information

GitHub: https://github.com/zziz/pwc
Stars: 15,398
License: Unknown
Last Commit: 2025-07-16

📊 Project Information

Project Name: pwc
GitHub URL: https://github.com/zziz/pwc
Programming Language: Unknown
⭐ Stars: 15,398
🍴 Forks: 2,468
📅 Created: 2018-09-02
🔄 Last Updated: 2025-07-16

🏷️ Project Topics

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🎥 Video Tutorials

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This article is automatically generated by AI based on GitHub project information and README content analysis

pwc

Project Description