Every year more than 17.9 million people die from Heart Disease, which mean almost half number of people in morocco. Talking of which,Heart Disease Deaths in Morocco reached 34,438 or 19.59% of total deaths in 2017. All of the previous details makes working on such a problem a huge priority.

Before J.C Humanity always suffers from Heart related disease, and from the then they were always searching for efficient ways to prevent it. Starting with Ancient Egyptians and Greeks and coming to our time. But the period of increased interest of Heart disease was from the 1900s. And from 1940s and 1950s The International Society of Cardiology is formed, and the World Congress of Cardiology starts being held under the patronage of the society. The link between heart disease and diet is discovered. More recently, people are start using Machine learning algorithms to help detecting and preventing this kind of disease.

There are many things that can raise your risk for heart disease. They are called risk factors. Some of them you cannot control, but there are many that you can control. That’s why we choose a data containing the most selective factors of this problem, and we are going process it using some of the most popular algorithms of machine learning, hoping to get some results about how to predict whether the next patient is in danger or not, and also what are the most correlated factors causing Heart disease.

In this repository we're trying to solve this problem using 3 machine learning models !

1. Logistic Regression
2. Random Forest
3. Neural Networks

Check the noetbook Heart_disease_final_project.ipynb For data cleaning and exploratory data analysis
Models Implementation.ipynb For the three models implementation and test