Welcome to SimpleML, your gateway to open-source machine learning projects. Whether you're a beginner or an expert, this repository offers a range of machine learning tasks for Hacktoberfest. Join our community and start your journey in machine learning today! 🚀
This repository consists of various machine learning projects, and all of the projects follow a simple and uniform structure. To contribute, please adhere to this structure:
- Project Name 📁 - The project folder, named in
kebab-case
.- Dataset 📦 - Stores the dataset used in the project. If the dataset is too large to upload, create a
README.md
file inside theDataset
folder and provide a link to the dataset. - Images 📷 - Contains images generated during data analysis, data visualization, or data segmentation.
- Model 🤖 - This folder houses your project files, which could be Jupyter notebooks, Python scripts, or any other relevant files for your machine learning project. Also, include a
README.md
file in this folder following this template. Uodate existing boilerplate with your code.
- Dataset 📦 - Stores the dataset used in the project. If the dataset is too large to upload, create a
- Explore the project repository and the README to understand the available projects.
- Check the existing issues in the Issues section.
- Comment on the issue you want to work on and wait for assignment.
- Fork the repository.
- Clone your forked repository.
- Make changes to your cloned repository.
- Add, commit, and push your changes.
- Create a pull request in GitHub.
If you're new to open source, here are some resources to help you get started:
- Watch this video to get started with open source
- How to Fork a Repo
- How to Clone a Repo
- How to Create a Pull Request
- Getting Started with Git and GitHub
Thanks goes to these Wonderful People. Contributions of any kind are welcome! 🚀
If you find this project helpful or learn something from it, consider giving it a star. Your support means a lot to us! ⭐
If you have any questions or need support, feel free to reach out to us at dsc@pes.edu.