This repository involves exploratory data analysis (EDA), visualizations, and the prediction of the presence of heart disease in patients using several machine learning algorithms.
The project aims to predict the presence of heart disease in patients using various machine learning algorithms. Exploratory data analysis (EDA) and visualizations are performed to gain insights into the data.
The dataset used for this project is named "heart.csv."
EDA and visualizations are carried out to understand the data distribution and relationships between features.
Several machine learning algorithms are employed to predict heart disease presence in patients.
The dataset used in this project is "heart.csv."
Comparison results of the machine learning algorithms used for prediction are provided.
Find more about the project on Kaggle at Heart Disease - Classifications.
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