This project aims to predict the likelihood of a heart attack based on various health indicators using machine learning techniques. The dataset used contains patient data with features such as age, cholesterol levels, blood pressure, and more.

we predict that the patient is suffering with heart attack or not

A model that can predict whether a person is likely to have a heart attack or not by using Logistic Regression.

Heart-Attack Prediction Model using TensorFlow on UCI Dataset

Heart attack risk prediction using machine learning (Random Forest Model)

Mechine Learning | Heart Attack Prediction

Halo semua! Ini adalah model klasifikasi menggunakan algoritma GradientBoostingRegressor yang dimana menghasilkan akurasi 99% untuk setiap kelasnya dan menghasilkan evaluasi dari model yang maksimal. Di repo ini juga, terdapat file deployment implementasi kedalam website di Streamlit! jangan lupa untuk follow Github ku ya!

CNN heart attack prediction model

Main repository for Kaggle's heart attack data science project (EDA + prediction).

Trying different ML algorithms to predict the chance of getting Heart Attack on basis of given input.

classification problem using knn, svm and simple neural networks

This is a program to predict whether a person is at low or high risk of having a heart attack.

This project contains the jupyter notebook and the data used for the Machine Learning C;lassification problem

In this notebook, I have reviewed several classification algorithms on datasets.

Data is analyzed to identify the likelihood of a patient who has had a heart attack, and what their survival rate will be after the event.

Bootcamp's final project - Use classical Machine Learning models to predict whether a patient is at risk of suffering a heart attack.

Creating machine learning model analysis using logistic regression and run the Streamlit apps to predict the probability of having heart attack in future.