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A machine learning project to predict medical insurance charges based on user features like age, BMI, and smoking status. Used Gradient Boosting Regressor for accurate cost prediction. Streamlit app enables real-time, interactive user input and predictions. Built with Python, Pandas, scikit-learn, and joblib.
Kumpatlapavankumar/Medical-Insurance-Cost-Estimation-Using-Machine-Learning
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A machine learning project to predict medical insurance charges based on user features like age, BMI, and smoking status. Used Gradient Boosting Regressor for accurate cost prediction. Streamlit app enables real-time, interactive user input and predictions. Built with Python, Pandas, scikit-learn, and joblib.
Topics
python
data-science
machine-learning
random-forest
numpy
linear-regression
exploratory-data-analysis
prediction
pandas
data-visualization
matplotlib
preprocessing
decision-trees
gradient-boosting-classifier
label-encoding
xgboost-regression
accuracy-score
train-test-split
model-selection-and-evaluation
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