Atharva Metkar

Logistic Regression Project

This project demonstrates the implementation of Logistic Regression for predictive analytics and classification. Below are some key features and insights:

• Dataset Analysis: Preprocessing and visualization of data for better insights.
• Model Training: Building and training a logistic regression model for binary classification.
• Evaluation Metrics: Accuracy, precision, recall, and confusion matrix for model performance.
• Use Cases: Prediction of employee promotion, medical diagnosis, and more.

The above screenshot showcases the Python implementation of Logistic Regression, including dataset preprocessing and feature scaling.