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# 🌌 Galactic Mining Hub

**Galactic Mining Hub** is an advanced Machine Learning-based platform designed to assist in the exploration and evaluation of potential mining sites across different celestial bodies. This project showcases the capabilities of ML in space mining exploration, providing predictive insights, recommendations, and detailed analysis of mining site data.

## 🚀 Project Overview

The **Galactic Mining Hub** was developed to serve as an advanced web platform for analyzing and recommending mining sites based on user preferences. The platform features interactive visualizations, insightful analyses, and personalized recommendations, making it a comprehensive tool for anyone interested in space mining.

Developed by: **Devanik**

## 🧩 Features

### 1. Prediction Model
- Predict potential mining sites based on various features.
- Generate insights and visualizations to understand the site's potential.
- Visualize key metrics and predictions.

### 2. Recommendation Model
- Evaluate mining sites using custom feature weights and a trained ML model.
- Offer personalized recommendations based on user input.
- Adjust recommendations according to user preferences and rank sites based on suitability.

### 3. Data Analysis
- Perform in-depth analysis to explore data characteristics.
- Detect clusters and identify outliers within the data.
- Generate detailed insights to guide decision-making.

### 4. Visualization
- Create advanced visualizations to understand data distributions and correlations.
- Customize visualizations to focus on specific features or comparisons.

### 5. Insights
- Gain actionable insights based on the characteristics of mining sites.
- Receive tailored recommendations for high-value, sustainable mining sites.

📊 Dataset
The project utilizes a synthetic dataset representing various celestial bodies and their potential mining sites. The dataset includes features such as:

Celestial Body: The name of the celestial body.
Iron (%): Percentage of iron composition.
Nickel (%): Percentage of nickel composition.
Water/Ice (%): Percentage of water or ice.
Estimated Value (B USD): Estimated economic value in billions of USD.
Sustainability Index: A metric representing the sustainability of mining operations.
Efficiency Index: A metric representing the efficiency of mining operations.
Distance from Earth (M km): Distance of the site from Earth in million kilometers.

🛠️ Technologies Used
Python: The core programming language used for the project.
Streamlit: For creating an interactive web application.
Pandas: For data manipulation and analysis.
Seaborn & Matplotlib: For creating visualizations.
Scikit-Learn: For machine learning models.

💻 How to Use
Select a model from the sidebar to explore its capabilities:

Prediction: To predict potential mining sites.
Recommendation: To get personalized recommendations.
Analysis: To explore and analyze the dataset.
Visualization: To create and customize visualizations.
Insights: To gain actionable insights based on the data.
Interact with the application by selecting features, adjusting parameters, and exploring the outputs.
**Galactic Mining Hub** is an advanced Machine Learning-based platform designed to revolutionize space mining exploration. By leveraging cutting-edge AI technologies, this project assists in the exploration and evaluation of potential mining sites across various celestial bodies. It provides predictive insights, personalized recommendations, and detailed analysis of mining site data, making it an invaluable tool for space mining enthusiasts, researchers, and industry professionals.

**Developed by:** [Devanik](https://www.linkedin.com/in/devanik)

<!-- If you have a project logo or banner, you can add it here using the following format:
![Galactic Mining Hub Logo](path/to/your/logo.png)
-->

## 📊 GitHub Stats

![Stars](https://img.shields.io/github/stars/Devanik21/ISRO_Mining_Site_FINAL_APP?style=for-the-badge)
![Forks](https://img.shields.io/github/forks/Devanik21/ISRO_Mining_Site_FINAL_APP?style=for-the-badge)
![Issues](https://img.shields.io/github/issues/Devanik21/ISRO_Mining_Site_FINAL_APP?style=for-the-badge)
![Pull Requests](https://img.shields.io/github/issues-pr/Devanik21/ISRO_Mining_Site_FINAL_APP?style=for-the-badge)
![Contributors](https://img.shields.io/github/contributors/Devanik21/ISRO_Mining_Site_FINAL_APP?style=for-the-badge)
![Last Commit](https://img.shields.io/github/last-commit/Devanik21/ISRO_Mining_Site_FINAL_APP?style=for-the-badge)

## 🛠️ Tech Stack

### Languages:
- **Python**: Core language for backend logic and machine learning.
- **HTML/CSS**: Frontend styling and structure for web components.
![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54)
![HTML5](https://img.shields.io/badge/html5-%23E34F26.svg?style=for-the-badge&logo=html5&logoColor=white)
![CSS3](https://img.shields.io/badge/css3-%231572B6.svg?style=for-the-badge&logo=css3&logoColor=white)
![Streamlit](https://img.shields.io/badge/Streamlit-FF4B4B?style=for-the-badge&logo=Streamlit&logoColor=white)
![Pandas](https://img.shields.io/badge/pandas-%23150458.svg?style=for-the-badge&logo=pandas&logoColor=white)
![NumPy](https://img.shields.io/badge/numpy-%23013243.svg?style=for-the-badge&logo=numpy&logoColor=white)
![scikit-learn](https://img.shields.io/badge/scikit--learn-%23F7931E.svg?style=for-the-badge&logo=scikit-learn&logoColor=white)
![Matplotlib](https://img.shields.io/badge/Matplotlib-%23ffffff.svg?style=for-the-badge&logo=Matplotlib&logoColor=black)
![Plotly](https://img.shields.io/badge/Plotly-%233F4F75.svg?style=for-the-badge&logo=plotly&logoColor=white)
![TensorFlow](https://img.shields.io/badge/TensorFlow-%23FF6F00.svg?style=for-the-badge&logo=TensorFlow&logoColor=white)
![Keras](https://img.shields.io/badge/Keras-%23D00000.svg?style=for-the-badge&logo=Keras&logoColor=white)
![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white)

### Frameworks:
- **Streamlit**: Used for developing the interactive web application.
## 🌟 Key Features

### Libraries:
- **Pandas**: Data manipulation and analysis.
- **NumPy**: Numerical computations and array processing.
- **Scikit-learn**: Machine learning models and evaluation metrics.
- **Matplotlib**: Plotting and data visualization.
- **Seaborn**: Statistical data visualization.
- **Plotly**: Interactive data visualization.
- **XGBoost**: Extreme Gradient Boosting for optimized machine learning models.
- **LightGBM**: High-performance gradient boosting framework.
- **🔮 Prediction Model:** Forecast potential mining sites using advanced ML algorithms
- **💡 Recommendation Engine:** Get personalized mining site suggestions based on custom preferences
- **📊 Data Analysis:** Perform in-depth exploratory data analysis with clustering and outlier detection
- **📈 Interactive Visualizations:** Create and customize advanced data visualizations
- **🧠 Actionable Insights:** Gain valuable insights to guide decision-making in space mining ventures

### Tools:
- **Joblib**: Model serialization for efficient storage and deployment.
- **Tesseract** (optional): Optical Character Recognition (OCR) for text extraction from images.
- **TensorFlow & Keras**: Deep learning frameworks for building and training AI/ML models.
- **App Framework:** Streamlit for rapid web app development.

### Version Control:
- **GitHub**: For code management, version control, and collaboration.
## 📊 Dataset

Review the insights and visualizations generated to inform your decision-making process regarding space mining opportunities.
The project utilizes a synthetic dataset representing various celestial bodies and their potential mining sites. Key features include:

- Celestial Body
- Mineral Composition (Iron %, Nickel %, Water/Ice %)
- Estimated Value (Billions USD)
- Sustainability Index
- Efficiency Index
- Distance from Earth (Million km)

## 🤝 Contributing
## 💻 Installation & Usage

We welcome contributions to the Galactic Mining Hub! If you’d like to contribute, please follow these guidelines:
1. Clone the repository:

1. **Fork the repository** to your own GitHub account.
2. **Clone the repository** to your local machine:
```bash
git clone https://github.com/YOUR_USERNAME/ISRO_Mining_Site_FINAL_APP.git
git clone https://github.com/Devanik21/ISRO_Mining_Site_FINAL_APP.git
```
3. **Create a new branch** for your changes:

2. Install dependencies:

```bash
pip install -r requirements.txt
```

3. Run the Streamlit app:

```bash
git checkout -b your-feature-branch
streamlit run app.py
```
4. **Make your changes** and test them thoroughly.
5. **Commit your changes** with clear commit messages.
6. **Push to your fork** and open a pull request.

For detailed contribution guidelines, please refer to the [Contributing.md](Contributing.md) file.
4. Navigate through the sidebar to explore different models and features:

- Prediction
- Recommendation
- Analysis
- Visualization
- Insights

5. Interact with the application by adjusting parameters and exploring the outputs to inform your space mining decisions.

## 📄 License & Contributing

| [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE) | [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg)](CODE_OF_CONDUCT.md) |
| :--------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------: |
| This project is licensed under the MIT License. Click the badge to view the full license text. | We welcome contributions! Please read our Contributing Guidelines and Code of Conduct before getting started. |

- [View License](LICENSE)
- [View Contributing Guidelines](CONTRIBUTING.md)
- [View Code of Conduct](CODE_OF_CONDUCT.md)

## 🛰️ Acknowledgments

- Inspired by the growing interest in space exploration and resource mining on celestial bodies
- Special thanks to the open-source community and the developers of the tools used in this project

## 📞 Contact

For questions or feedback, please reach out to [Devanik](https://www.linkedin.com/in/devanik) on LinkedIn.

---

⭐️ If you find this project interesting, please consider giving it a star on GitHub!

👤 Author
Devanik - LinkedIn
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
## 📚 Project Documentation

🛰️ Acknowledgments
Inspiration for this project came from the growing interest in space exploration and the potential for resource mining on other celestial bodies.
Special thanks to the open-source community and the developers behind the tools used in this project.
| Document | Description |
| ---------------------------------------- | ------------------------------------------ |
| [README.md](README.md) | Project overview and main documentation |
| [CONTRIBUTING.md](CONTRIBUTING.md) | Guidelines for contributing to the project |
| [LICENSE](LICENSE) | Full text of the MIT License |
| [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) | Code of Conduct for contributors |

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