Key Features:

Data Preprocessing: Includes data cleaning, handling missing values, and feature scaling for optimal model performance.

Logistic Regression Model: Implements a Logistic Regression model using scikit-learn library.

Model Evaluation: Evaluates model performance using metrics such as accuracy, precision, recall, F1-score, and AUC-ROC.