/Heart-Disease-Prediction-using-Neural-Networks

This project will focus on predicting heart disease using neural networks. Based on attributes such as blood pressure, cholestoral levels, heart rate, and other characteristic attributes, patients will be classified according to varying degrees of coronary artery disease. This project will utilize a dataset of 303 patients and distributed by the UCI Machine Learning Repository. Machine learning and artificial intelligence is going to have a dramatic impact on the health field; as a result, familiarizing yourself with the data processing techniques appropriate for numerical health data and the most widely used algorithms for classification tasks is an incredibly valuable use of your time! In this tutorial, we will do exactly that. We will be using some common Python libraries, such as pandas, numpy, and matplotlib. Furthermore, for the machine learning side of this project, we will be using sklearn and keras.

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Heart-Disease-Prediction-using-Neural-Networks

This project will focus on predicting heart disease using neural networks. Based on attributes such as blood pressure, cholestoral levels, heart rate, and other characteristic attributes, patients will be classified according to varying degrees of coronary artery disease. This project will utilize a dataset of 303 patients and distributed by the UCI Machine Learning Repository. Machine learning and artificial intelligence is going to have a dramatic impact on the health field; as a result, familiarizing yourself with the data processing techniques appropriate for numerical health data and the most widely used algorithms for classification tasks is an incredibly valuable use of your time! In this tutorial, we will do exactly that. We will be using some common Python libraries, such as pandas, numpy, and matplotlib. Furthermore, for the machine learning side of this project, we will be using sklearn and keras.