Heart_disease_prediction and heart-disease-prediction-ml
These two tools are competitors, as both repositories provide distinct machine learning implementations for predicting heart disease, leading users to choose one over the other based on algorithmic preference or project needs.
About Heart_disease_prediction
chayandatta/Heart_disease_prediction
Heart Disease prediction using 5 algorithms
Compares five classification algorithms (Logistic Regression, Random Forest, Naive Bayes, KNN, Decision Tree) on the UCI Heart Disease dataset, with hyperparameter tuning to optimize accuracy across models. Delivered as a Jupyter notebook enabling interactive exploration of model performance and feature importance visualization. Targets ML beginners seeking hands-on experience with supervised learning fundamentals and algorithm comparison workflows.
About heart-disease-prediction-ml
goldteaa/heart-disease-prediction-ml
Machine learning pipeline for predicting heart disease using Logistic Regression and Random Forest with Python, Pandas, and Scikit-learn.
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