Developed a machine learning project to predict diabetes using a real-world dataset. The project involved data exploration, data cleaning, data visualization, building a Logistic Regression classification model, and evaluating its performance. Achieved an accuracy of 81.82% using Python and libraries including Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn. Collaborated with a team throughout the project lifecycle, applying data analysis and machine learning techniques to solve a real-world healthcare problem.
