using Machine Learning

This project focuses on training a machine learning model for predicting heart disease. To achieve the best possible result, the data has been trained using three different algorithms:

• Logistic Regression
• SVM (Support Vector Machine)
• Random Forest

This project was completed as part of the final lab of an Artificial Intelligence course at Misurata University's Faculty of Information Technology. The primary resource utilized from thecleverprogrammer.com, and the dataset was sourced from kaggle.com. After implementing necessary adjustments and improvements to achieve optimal results, a comprehensive Arabic report was uploaded to Google Drive.

To execute interactive python notebook on your local device, we recommend using Jupyter Notebook.

Use the package manager pip to install requirements.

pip install -r requirements.txt

I recommend using Anaconda for your project. It's designed specifically for data science and scientific computing, and includes a package manager and environment management tools that make it easy to install and manage packages and dependencies. Plus, it comes with pre-installed libraries and tools like Jupyter Notebook, Spyder, and RStudio, so you can get started quickly and easily.

These results that were obtained during the training process of the machine learning models.