Diabetic Patient Readmission Prediction Using Machine Learning

A Data Science project focused on exploring and preparing diabetic patient data to support the prediction of hospital readmission within 30 days

The project includes data cleaning, exploratory data analysis (EDA), missing value handling, outlier detection, and feature engineering to prepare high-quality data for machine learning

Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, and Jupyter Notebook

Data exploration and preprocessing completed, with model development planned for the next phase