The datasets consists of several medical predictor variables and one target variable, Outcome. Predictor variables includes the number of pregnancies the patient has had, their BMI, insulin level, age, and so on. The main objective is to predict whether the given person is having diabetes or not.

The main objective of the dataset is to predict Chances of Survival based on several explanatory factors such as Pclass, Sex, Age, SibSp, Parch, etc. using Machine Learning algorithms. The methods we intend to use are: Binary Logistic Regression, Naive Bayes, Decision Tree, Random Forest