Group 16 - Deep Learning

Welcome to the Group 16 - Deep Learning repository! This repository serves as a central hub for our team to share resources, collaborate on code, and showcase our work in the field of deep learning. We aim to create an environment where we can learn, grow, and achieve our goals together.

Repository Purpose

The main purposes of this repository are:

1. Resource Sharing: We can share important resources, such as research papers, datasets, libraries, and tutorials, that are relevant to our deep learning projects. This will help us stay updated and leverage the latest advancements in the field.

2. Code Collaboration: We can collaborate on code by sharing our projects, experiments, and implementations. This allows us to learn from each other, provide feedback, and collectively improve our coding skills.

3. Showcasing Our Work: This repository will serve as a portfolio to showcase our collective achievements and progress. We can highlight completed projects, successful experiments, and any other notable contributions.

Git Feature Branch Workflow

To ensure smooth collaboration and version control, we will follow the Git feature branch workflow. Here's a brief overview of how this workflow should be applied:

1. Create a Feature Branch: When working on a new feature, improvement, or bug fix, create a new branch based on the latest main branch. Use a descriptive name for the branch that reflects the purpose of your work.

2. Work on the Branch: Make your changes, commits, and iterations on the feature branch. Regularly push your commits to the remote repository to enable collaboration with other team members.

3. Keep the Branch Updated: Regularly sync your feature branch with the latest changes from the main branch. This can be done by merging the latest main branch into your feature branch.

4. Code Review: Once you have completed your work on the feature branch, request a code review from at least one team member. This ensures quality control and allows for feedback and improvements.

5. Merge to Main: After your code has been reviewed and approved, merge your feature branch into the main branch. Resolve any conflicts that may arise during the merge process.

6. Delete Feature Branch: Once the feature branch has been merged, it is no longer needed. You can safely delete the branch to keep the repository organized.

By following this workflow, we can maintain a structured development process and ensure that our codebase remains clean and stable.

Contribution Guidelines

We encourage every team member to actively contribute to this repository. To contribute, follow these guidelines:

1. Clone the Repository: Clone the repository to your local machine.

2. Create a Feature Branch: Create a new branch for your contribution.

3. Make Changes: Make your desired changes, improvements, or additions to the repository.

4. Commit Changes: Commit your changes with a descriptive commit message.

5. Push Changes: Push your changes to the feature branch.

6. Create a Pull Request: Create a pull request from your feature branch to the main branch of this repository. Provide a clear description of your changes.

7. Code Review: Your pull request will be reviewed by team members. Address any feedback or changes requested.

8. Merge Changes: Once your pull request has been approved, it will be merged into the main branch. Congratulations on your contribution!

Please note that all contributions to this repository should align with the project's goals and guidelines. We expect respectful and professional behavior from all contributors.

Dependency management

1. Ensure you have installed correct NVIDIA drivers / CUDA >= 11.8 / CuDNN (version determined by corresponding CUDA version)

2. Create a virtual environment with venv and activate it

3. Then run the following:

pip install -r requirements.txt --index-url https://download.pytorch.org/whl/cu118

Datasets

These are the links to the datasets to be used for this project:

1. English-Hindi Corpus

2. Speech Dataset

3. NLP for Hindi

4. AI4Bharat

You are free to add any other dataset you find useful for the project.

Other resources

• Micrograd

• Tinygrad

• Awesome List

• Awesome NLP

• Papers With Code

• Learn OpenCV

• Made with ML

• ChatPDF

• Semantic Scholar

Conclusion

We hope this repository becomes a collaborative space where we can share knowledge, work on exciting projects, and make significant contributions to the field of deep learning. Let's learn, grow, and achieve together as Group 16!

For any questions or concerns, please reach out to the repository administrator (Nick Yazdani).

Happy coding!