In this problem you are required to apply various classification techniques on a benchmark

dataset: Diabetes Risk Prediction given as a CSV file in the attachment $($source: Kaggle$).$

This dataset is a collection of medical and demographic data from patients, along with their

diabetes status $($positive or negative$).$ The data includes features such as age, gender, polyuria,

polydipsia, sudden weight loss, weakness, polyphagia, visual blurring, itching, irritability,

delayed healing etc. This dataset can be used to build machine learning models to predict

diabetes in patients based on their medical history and demographic information.