Data Science Pipeline Playground

Welcome to the Data Science Pipeline Playground! This repository is designed to help data science enthusiasts, from beginners to advanced practitioners, explore and contribute to various data science projects. Our goal is to create a collaborative space for learning, experimenting, and building end-to-end data science pipelines.

🎯 Purpose

This repository serves multiple purposes:

1. Provide a platform for Hacktoberfest contributions
2. Offer hands-on experience with real-world data science projects
3. Demonstrate the entire data science pipeline from data collection to model deployment
4. Foster collaboration and knowledge sharing within the data science community

🗂️ Repository Structure

The repository is organized into three main categories based on difficulty level:

• Beginner: Ideal for those new to data science
• Intermediate: Suitable for those with some experience
• Advanced: Challenging projects for seasoned data scientists

Each project within these categories follows a consistent structure:

project_name/

├── README.md

├── requirements.txt

├── main.py

└── data/

🚀 Getting Started

1. Clone the repository: git clone https://github.com/MohammedHamzaMalik/data-science-pipeline-playground.git
2. Navigate to the project directory: cd data-science-pipeline-playground
3. Choose a project from one of the difficulty levels
4. Follow the instructions in the project's README.md file

🤝 How to Contribute

We welcome contributions from data scientists of all skill levels! Here's how you can contribute:

1. Fork the repository
2. Create a new branch for your feature: git checkout -b feature-name
3. Make your changes and commit them: git commit -m 'Add some feature'
4. Push to the branch: git push origin feature-name
5. Submit a pull request

Please read our CONTRIBUTING.md file for detailed guidelines on how to contribute. (TBD - Coming Soon)

🤝 Contribute Your Projects

We welcome contributions from data scientists looking to share their projects!

If you have a data science project that you would like to contribute, please follow these steps:

1. Fork the repository: Click the "Fork" button at the top right of the page.
2. Clone your forked repository: Run the following command in your terminal: git clone https://github.com/yourusername/data-science-pipeline-playground.git
3. Create a new branch: Before adding your project, create a new branch: git checkout -b add-your-project-name
4. Add your project: Create a new directory for your project under the appropriate difficulty level (beginner/intermediate/advanced), and make sure to include a README.md with instructions.
5. Commit your changes: Commit your new project and its details: git add . git commit -m 'Add your project name'
6. Push to your fork: Push your changes back up to your fork: git push origin add-your-project-name
7. Submit a Pull Request: Go to the original repository and submit a pull request, detailing what your project is about and how to use it.

We are excited to see your contributions and help grow the community! 😊

📚 Available Projects

Beginner

• Exploratory Data Analysis on Titanic Dataset (In Development)
• Basic Data Visualization with Matplotlib (Planned)
• Simple Linear Regression Model (Planned)

Intermediate

• Time Series Forecasting (TBD)
• Sentiment Analysis using NLP (TBD)
• Image Classification with CNNs (TBD)

Advanced

• End-to-end ML Pipeline with MLflow (TBD)
• Reinforcement Learning for Game AI (TBD)
• Big Data Processing with PySpark (TBD)

🛠️ Technologies Used

• Python
• Pandas, NumPy
• Scikit-learn
• TensorFlow, PyTorch (Planned)
• Matplotlib, Seaborn
• Jupyter Notebooks

📊 Project Showcase

Here are some of our featured projects:

1. [Project Name 1] - Coming Soon
2. [Project Name 2] - Coming Soon
3. [Project Name 3] - Coming Soon

🏆 Hall of Fame

We appreciate all our contributors! Check out our Hall of Fame to see the awesome people who have contributed to this project. (Coming Soon)

📜 License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details. (TBD)

📞 Contact

If you have any questions or suggestions, please open an issue or contact the maintainers:

• Mohammed Hamza Malik - Project Lead

Happy coding and data science exploration! 🎉📊🔬