https://github.com/hariprasath-v/dphi-data-sprint-37-medical-insurance-cost

To Estimate the individual medical costs of customers who have bought the health insurance.
https://github.com/hariprasath-v/dphi-data-sprint-37-medical-insurance-cost

exploratory-data-analysis machine-learning matplotlib pandas seaborn sklearn xgbregressor

Last synced: 4 months ago
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To Estimate the individual medical costs of customers who have bought the health insurance.

• Host: GitHub
• URL: https://github.com/hariprasath-v/dphi-data-sprint-37-medical-insurance-cost
• Owner: hariprasath-v
• Created: 2021-06-15T15:16:21.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2022-01-15T14:41:09.000Z (over 3 years ago)
• Last Synced: 2025-01-13T01:44:56.707Z (5 months ago)
• Topics: exploratory-data-analysis, machine-learning, matplotlib, pandas, seaborn, sklearn, xgbregressor
• Language: Jupyter Notebook
• Homepage:
• Size: 312 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Dphi-Data-Sprint-37-Medical-Insurance-Cost

# This competition was hosted on the Dphi website.

# Overview

## To Estimate the individual medical costs of customers who have bought the health insurance.

# what is in the notebook?

## Exploratory Data Analysis

## Feature Engineering

## Modeling

## Hyperparameter Tuning(Gridsearchcv)

## Cross_Validation Results Visualization

# Packages Used,

## Pandas

## numpy

## Seaborn

## matplotlib

## sklearn

## xgboost