Insurance Premium Prediction

Insurance Premium Prediction

Problem Statement:

The goal of this project is to give people an estimate of how much they need based on their individual health situation. After that, customers can work with any health insurance carrier and its plans and perks while keeping the projected cost from our study in mind. This can assist a person in concentrating on the health side of an insurance policy rather han the ineffective part.

Dataset:

The primary source of data for this project was from Kaggle repository. You can download the dataset from here

Approach:

Performing machine learing tasks like Exploratory Data Exploration(EDA), Data Cleaning, Feature Engineering, Model Building and model testing to build a solution that should able to predict the premium of the personal for health insurance.

• Data Exploration: Explored and Analyzed dataset using, pandas, numpy, matplotlib and seaborn libraries

• Data Visualization: Plotted different graphs to get more insights about dependent and independent variables/features.

• Feature Engineering: Performed Feature Encoding, Feature Scaling and Feature Selection

• Model Building: In this step, first dataset Splitting is done. After that model is trained on different Machine Learning Algorithms such as:

• Model Evaluation

• Model Testing

• Web Application Building

• Web Application Deployment