I will build a high-accuracy machine learning model to predict heart disease based on medical data. I specialize in using Python, Pandas, Scikit-learn, and ensemble models like Random Forest, Boosting, and Stacking.
My process includes:
✔ Data cleaning and preprocessing
✔ Exploratory Data Analysis (EDA)
✔ Model training and evaluation (confusion matrix, accuracy score, ROC-AUC)
✔ Hyperparameter tuning
✔ Final report in PDF/Word format with visual graphs
✔ Source code and documentation
I have already worked on Heart Disease datasets and achieved up to 99% accuracy using advanced models. I ensure clean, well-commented code and detailed analysis with medical insights. If needed, I can also build an interactive Streamlit web app for real-time predictions.
Tools I use: Python, Scikit-learn, Pandas, Matplotlib, Seaborn, Streamlit
Skills: Machine Learning, Data Analysis, Classification, Feature Engineering, Model Evaluation, Python
Let’s work together to turn raw data into reliable predictions!