This project aims to predict the medical costs for individuals based on factors such as age, sex, BMI, and smoking status. The analysis includes data loading, exploratory data analysis (EDA), and data preprocessing using Python.
In this repository, you will find:
✅ Source File: The complete Python code for the project in a Jupyter Notebook.
✅ Dataset: The insurance dataset in a CSV file used for the analysis.
Data Loading: Efficiently loading and managing the dataset. Exploratory Data Analysis (EDA): Detailed examination and visualization of the data. Data Preprocessing: Cleaning and preparing the data for modeling.
To explore the project:
- Clone this repository to your local machine.
- Open the Jupyter Notebook to review the code and analysis.
- Use the CSV file to experiment with the dataset.
Check out the detailed report with Python code on my website:
My Portfolio: https://imranayasmin.wordpress.com/insurance-medical-cost-prediction-project-python/