🚀 Rock vs Mine Detection ML Project

This is my first Machine Learning project where I built a Rock vs Mine Detection System using Logistic Regression. The model predicts whether an object is a rock or a mine based on sonar data.

📌 Features

• ✅ Uses Sonar dataset for classification
• ✅ Implements Logistic Regression algorithm
• ✅ Achieves high accuracy on test data
• ✅ Simple predictive system for underwater object detection

📊 Dataset

The dataset contains 60 numerical features extracted from sonar signals bounced off different objects.

• R → Represents Rock
• M → Represents Mine

The dataset is split into:

• Training set
• Test set

🔧 Installation & Setup

To run this project:

1. Clone the repository:

   git clone https://github.com/viraj-gavade/rock-vs-mine.git
   cd rock-vs-mine

2. Install dependencies:

   pip install numpy pandas scikit-learn matplotlib jupyter

3. Run the Jupyter Notebook:

   jupyter notebook Rock_vs_Mine_Detection.ipynb

🏆 Results

• Training Accuracy: 83.5%
• Test Accuracy: 76.2%

📸 Sample Prediction

If the input is:

input_data = (0.0200, 0.0371, 0.0428, 0.0207, 0.0954, 0.0986, 0.1539, 0.1601, 0.3109, 0.2111, 0.1609, 0.1582, 0.2238, 0.0645, 0.0660, 0.2273, 0.3100, 0.2999, 0.5078, 0.4797, 0.5783, 0.5071, 0.4328, 0.5550, 0.6711, 0.6415, 0.7104, 0.8080, 0.6791, 0.3857, 0.1307, 0.2604, 0.5121, 0.7547, 0.8537, 0.8507, 0.6692, 0.6097, 0.4943, 0.2744, 0.0510, 0.2834, 0.2825, 0.4256, 0.2641, 0.1386, 0.1051, 0.1343, 0.0383, 0.0324, 0.0232, 0.0027, 0.0065, 0.0159, 0.0072, 0.0167, 0.0180, 0.0084, 0.0090, 0.0032)

The model outputs:

The Object is A Rock!

🌟 Future Improvements

• Try different ML algorithms (Random Forest, SVM, Neural Networks)
• Implement hyperparameter tuning to improve accuracy
• Deploy the model as a web app using Flask or Streamlit
• Add data visualization for better understanding of feature importance
• Implement cross-validation for more reliable performance metrics

💡 Learnings

• ✔ Understanding of data preprocessing
• ✔ Working with pandas & NumPy
• ✔ Implementing train-test split & logistic regression
• ✔ Model evaluation techniques

🛠️ Project Structure

rock-vs-mine/
├── Rock_vs_Mine_Detection.ipynb
├── sonar_train.csv
├── sonar_test.csv
├── README.md
└── requirements.txt

📌 Author

Viraj Gavade

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