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abroniewski / Heart-Disease-Machine-Learning-Exploration

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A comprehensive exploration of machine learning techniques and data science best practices applied to the UCI Heart Disease dataset. Focusing on data preprocessing, exploratory analysis, and predictive modelling to identify key factors in heart disease. Part of Big Data Management and Analytics (BDMA) program.

machine-learning neural-network random-forest logistic-regression uci decision-trees bdma heartdisease
  • Updated May 23, 2024
  • Jupyter Notebook

Parthadee / AI-in-Healthcare-of-Heart-Disease

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This project applies machine learning to predict heart disease using clinical data. It covers data preprocessing, model building, and performance evaluation, aiming to support early diagnosis and healthcare decision-making through data-driven insights and AI-based prediction techniques.

python numpy excel scikit-learn pandas seaborn datascience healthcare matplotlib machinelearning predictive-modeling powerbi datavisualization artificialintelligence medicalai heartdisease healthcareanalytics
  • Updated Jun 11, 2025
  • Jupyter Notebook

ankushmallick1100 / Heart-disease-prediction-using-maching-learning

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This is a machine learning project that uses various machine learning alogorithms to predict whether a patient is suffering from heart disease or not. Here I am using variour machine learning algorithms like Random Forest classifier, XGBClassifier, GaussianNB, Decision Tree Classifier, K-Nearest Neighbours and Logistic Regression.

python machine-learning jupyter random-forest numpy machine-learning-algorithms gaussian heart naive-bayes-classifier logistic-regression machinelearning decision-tree-classifier machine-learning-models knearest-neighbor-classifier heartdisease xgboost-classifier heartdisease-prediction
  • Updated Apr 15, 2023
  • Jupyter Notebook

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