Complex Data Lab

AI & ML interests

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McGill University Complex Data Lab 🤗

Welcome to the official Hugging Face organization of McGill University Complex Data Lab (CDL)!

We are an interdisciplinary research group at McGill University, dedicated to advancing the field of machine learning, data science, and complex systems analysis. Our work spans multiple domains, including natural language processing (NLP), computer vision, bioinformatics, and social data analysis.

Mission 🌍

Our mission is to develop innovative tools and methodologies for understanding and modeling complex datasets. We strive to push the boundaries of knowledge by:

  • Building state-of-the-art machine learning models and algorithms.
  • Applying data science techniques to real-world problems in various fields.
  • Collaborating with researchers, students, and industry partners to foster innovation.

Projects 🚀

Here, you'll find our ongoing and past projects, including:

  • MisInfo Dataset: Brief description of the project, its goals, and any models or datasets associated.
  • Project Name 2: Brief description of the project, its goals, and any models or datasets associated.
  • Project Name 3: Brief description of the project, its goals, and any models or datasets associated.

Feel free to explore the repositories under our organization to learn more about our work!

Contributing 🤝

We welcome contributions from researchers, developers, and enthusiasts interested in collaborating on our projects. To contribute:

  1. Fork the repository you want to contribute to.
  2. Create a branch for your feature or bug fix.
  3. Make your changes and commit them.
  4. Open a pull request with a detailed description of your work.

Please refer to our Contributing Guidelines for more information.

Publications and Resources 📚

Here is a list of some of our recent publications and resources:

For a full list of our publications, please visit our website.

Contact Us ✉️

For inquiries, collaborations, or more information about our work, please reach out to us:

models

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