Used a neural network built with TensorFlow to predict diabetes based on patient health indicators. The data is preprocessed, scaled, and used to train a model with dropout and early stopping to prevent overfitting. The model achieves strong performance, evaluated through accuracy, classification reports, confusion matrix, and ROC curve.
