Interactive Machine Learning App for Heart Disease PredictionInteractive Machine Learning App for Heart Disease Prediction
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Zahra Abbas
• May 26
Developed a machine learning-based Heart Disease Prediction System with an interactive Streamlit interface for real-time prediction and analysis. The project involved data cleaning, exploratory data analysis, feature engineering, model training, and evaluation using Python and machine learning libraries.
The goal was to create a simple and user-friendly system that could help analyze patient health indicators and predict possible heart disease risk. Alongside the predictive model, the project also focused heavily on data visualization and interpretability.
Key tasks included: • Data preprocessing and cleaning • Exploratory Data Analysis (EDA) • Correlation analysis and visualization • Machine learning model building and evaluation • Interactive Streamlit web app development • Report writing and presentation preparation
Tools & Technologies: Python, pandas, matplotlib, scikit-learn, Streamlit
This project was collaboratively developed with my teammate Gaurina as part of a university machine learning project.
Data AnalysisData EngineeringPythonMachine Learning Engineeringscikit-learn
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