In this project we will predict the cost required for a patient depending on his/her health conditions.

We will explore a data set dedicated to the cost of treatment of different patients. The cost of treatment depends on many factors: diagnosis, type of clinic, city of residence, age and so on.

Predict individual medical insurance charges using linear regression. This project explores how demographic and lifestyle factors impact insurance costs, applying data cleaning, EDA, feature selection, and regression modeling. All code and results are in the analysis notebook.

Memprediksi biaya pengobatan yang harus ditanggung asuransi

in this project i trained a medical cost dataset using linear regression algorithm to come with predictions about the amount of medical costs

What medical costs should a health insurance company expect from their policy holders?

This work demonstrates how to apply linear regression using Python and scikit-learn, starting from a simple synthetic example and progressing to a real-world healthcare dataset.

This project estimates medical costs based on patient health records and demographic data.

Predict insurance charges with linear regression; Python project offers a concise EDA-to-model workflow with feature engineering, training, and evaluation 🐙.