- Executed a comprehensive analysis of the Heart Disease Dataset by harnessing the power of Pandas and NumPy for meticulous data manipulation, encompassing cleaning, transformation, and in-depth exploratory analysis.
- Employed Seaborn and Matplotlib to craft compelling visualizations, unveiling key patterns and insights that informed the analysis.
- Developed a robust Logistic Regression model, meticulously trained and tested, resulting in an impressive accuracy rate exceeding 90%.
- Conducted a thorough evaluation of the model’s performance using a suite of metrics, including the accuracy score, confusion matrix, and classification report, ensuring the model’s reliability and effectiveness in predictive tasks.