SONAR Rock vs Mine Prediction with Python

This project focuses on building a machine learning system that predicts whether an underwater object is a Rock or a Mine using SONAR data.

The model was developed using Python in Google Colab, where the dataset was preprocessed and analyzed before training a Logistic Regression classifier. Model performance was evaluated using accuracy metrics and a confusion matrix to assess classification results.

Key steps in this project include:

- Data preprocessing and feature handling

- Training a Logistic Regression model

- Model evaluation using accuracy score and confusion matrix

- Making predictions on unseen SONAR data

This project demonstrates my ability to build and evaluate classical machine learning models for binary classification problems using real-world data.