Diabetes is a common chronic disease that many people suffer from every year. Anything that leads to high sugar level in the body – such as unhealthy lifestyle, consumption of fast foods, or genetic differences – can be a cause for diabetes (Both Type 1 and 2). The consequences for ignoring the symptoms can be very extreme.

However, with the help of Machine Learning, we can now create an algorithm to predict the onset of diabetes using parameters whose relation we could not understand.

The aim of this project is to find out and apply the most accurate method for the prediction of diabetes. The methods used in the code are: 1. Logistic Regression 2. Random Forest Classifier 3. SVM 4. Naïve Bayes’ Classifier