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heart-disease-prediction-model's Introduction

heart-disease-prediction-model

The goal of this project is to build a model that can predict the probability of heart disease occurrence, based on a combination of features that describes the disease. In order to achieve the goal, we used data sets that was collected by Cleveland Clinic Foundation in Switzerland.

Software and libraries used in this project

Python language was used in this project, with many of its libraries listed below:

Pandas: data analysis library Numpy: scientific computing library Sklearn: machine learning library Itertools: library contains functions for creating iterators to use for efficient looping Matplotlib: 2D plotting library Seaborn: statistical data visualization

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