HealthyLife Insurance company has gathered the data regarding the customers and wants to analyze it. Different customers have different lifestyles and hence not all can have the same medical expenditures or requirement of health insurance. To better tailor the insurance package to be given to different customers, the company now wants to integrate machine learning into the process and identify the right insurance charges for each customer. You are hired as a ML Engineer to help the company predict the right charges based on the data that they have been maintaining for each customer.

• Dataset Information

Column ------------------------------> Description

Age ---------------------------------> Age of Primary Beneficiary

Sex ---------------------------------> Insurance Contractor gender (female, male)

BMI ---------------------------------> Body Mass Index, providing an understanding of body, weights that are relatively high or low relative to height, objective index of body weight (kg / m^2) using the ratio of height to weight, ideally 18.5 to 24.9

Children ----------------------------> Number of children covered by health insurance / Number of dependents

Smoker ------------------------------> Whether the beneficiary smokes or not

Region-------------------------------> The beneficiary’s residential area in the US, northeast, southeast, southwest, northwest.

charges -----------------------------> Individual medical costs billed by health insurance (target variable)

• Problem Statement

Predict how much could be the insurance charges for a beneficiary based on the data provided using Linear Regression.