Predict whether a person has diabetes or not.
Dataset based on glucose, BP, skin thickness, insulin, BMI, diabetes pedigree function, age, and pregnancy. Pre-processed and transformed the dataset by replacing null values with mean and median. Built, trained, and evaluated Logistic Regression, Decision Tree Classifier, Random Forest Classifier, and Support Vector Machine models using scikit-learn. Fine-tuned Random Forest Classifier prediction model to achieve a 98.75% accuracy.