Add Sonic.AI: Sonar Signal Classification Project (Mine vs. Rock)
This PR adds the Sonic.AI project, a machine learning model that classifies sonar signals as either "Rock" or "Mine", a task crucial in submarine object detection and naval defense systems.
🚀 Project Overview: Dataset: Sonar signals dataset from UCI Machine Learning Repository
Goal: Predict whether the object detected by sonar is a metal mine or a rock
Algorithm: Logistic Regression (baseline model)
Evaluation Metric: Accuracy, Confusion Matrix
🧠 Key Features: Preprocessing of 60-feature sonar frequency data
Binary classification using logistic regression
Train/test split and model validation
Confusion matrix visualization
CLI prediction script for custom input
📁 Files Added: sonic_classifier.py — Model training and evaluation script
predict.py — Command-line prediction script
requirements.txt — Dependencies
README.md — Project overview and usage instructions
data/sonar.all-data.csv — Dataset file (or script to download if not committed)
✅ Future Improvements: Explore advanced models like Random Forests or SVM
Deploy via Streamlit for interactive prediction
Add grid search and cross-validation