ML Fusion Lab - Learn Machine Learning
Welcome to ML Fusion Lab!.
Website Preview
๐ Stars |
๐ด Forks |
๐ Issues |
๐ Open PRs |
๐ Close PRs |
๐ Languages |
๐ Contributors |
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๐Featured In
Event Logo |
Event Name |
Event Description |
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GirlScript Summer of Code 2024 Extd |
The coding period is from October 1st to November 10, during which contributors make contributions and earn points on the platform. |
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Hacktoberfest 2024 |
Hacktoberfest is a month-long celebration of open source software run by DigitalOcean, GitHub, and Twilio. It encourages contributions to open source projects and promotes a global community of developers. |
Table of Contents
- Website Preview
- Featured In
- Introduction
- Technology Used
- Key Features
- Overview
- Getting Started
- How to Report Bugs
- How to Request Enhancements
- Contributors
- Stargazers
- Forkers
- Support
Introduction๐
This project aims to provide an interactive platform where users can learn machine learning from scratch, explore projects, and contribute their own machine learning endeavors.
Technology Used๐
๐ Key Features
- Comprehensive ML Courses: Learn machine learning from beginner to advanced levels.
- Hands-on Projects: Real-world projects to test and enhance your skills.
- Community Contributions: Upload and collaborate on ML projects.
Overviewโญ
Live Project -- https://ml-fusion-lab.netlify.app/
Getting Started
Guidelines
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Before creating an issue, use the search feature to check if a similar issue already exists.
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Issues are assigned on the basis of โfirst come, first served.โ Others may get a chance if the issue gets stale and the assignee is inactive for over a week.
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Do not create a Pull Request until the issue has been assigned to you.
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Always mention the issue number for which the Pull Request is being created. You can use one of the following keywords in your PR description or comment to reference the issue: closes #123
fixes #123
resolves #123
implements #123
Remember to follow this practice to streamline collaboration and keep the project organized! ๐
Contributing
Contributions are welcome! To contribute, You can follow these steps:
Fork the Repository
- Navigate to the ML Fusion Lab repository.
- Click the "Fork" button at the top right of the page.
Clone Your Fork
- Open GitHub Desktop.
- Click on "File" > "Clone Repository".
- Select the forked repository and choose the local path where you want to save it.
- Click "Clone".
Create a Branch
- In GitHub Desktop, click on "Current Branch" and select "New Branch".
- Name your branch descriptively, e.g.,
feature-add-animation
.
- Click "Create Branch".
Making And Committing the Changes
Open the Repository in Your Editor
- In GitHub Desktop, click on "Repository" > "Open in Visual Studio Code" (or your preferred editor).
Implement Your Changes
- Make your changes in the code editor.
- Save your changes.
Commit Your Changes
- In GitHub Desktop, you should see your changes listed.
- Enter a summary for your commit and a detailed description if necessary.
- Click "Commit to
your-branch-name
".
Push Your Changes
- Click "Push origin" in GitHub Desktop to push your changes to your forked repository on GitHub.
Submit a Pull Request
- Navigate to your forked repository on GitHub.
- Click on the "Compare & pull request" button.
- Ensure the base repository is
ML-Fusion-Lab/ML-Fusion-Lab-Website
and the base branch is main
.
- Add a title and description for your pull request.
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Click "Create pull request".
How to Report Bugs
- Check Existing Issues: Before opening a new issue, check if the bug has already been reported.
- Open a New Issue: If the bug is new, open an issue on the Issues page.
- Provide Details: Include as much information as possible, such as steps to reproduce the bug, expected behavior, and screenshots if applicable.
How to Request Enhancements
- Check Existing Issues: Before suggesting a new feature, check if it has already been proposed.
- Open a New Issue: If the feature is new, open an issue on the Issues page.
- Provide Details: Clearly describe the enhancement and why it would be beneficial.
Contributors
A heartfelt thank you to the following individuals for their valuable contributions to this project. Your support and dedication are greatly appreciated:
๐ฅ Team
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Vivek Vardhan Project Admin |
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Support๐งก
If you find this project helpful, please consider giving it a โญ on GitHub, Happy Coding!
Thank you for contributing to the ML Fusion Lab! Your efforts help make this project better for everyone. ๐๐