CardioCare

Overview

CardioCare is a project designed to predict heart disease using machine learning. It incorporates a predictive model that analyzes various health metrics and provides insights into the likelihood of heart disease. This project also includes a Jupyter Notebook for exploratory data analysis and model training.

Features

• Heart Disease Prediction: Uses machine learning algorithms to predict the risk of heart disease.
• Jupyter Notebook: Contains code for data preprocessing, model training, and evaluation.
• User Management: Allows users to register and log in to access personalized features.

Technologies Used

• Frontend: HTML, CSS, JavaScript
• Backend: [Django]
• Database: [MySQL]
• Machine Learning: Python, scikit-learn, pandas, NumPy

Installation & Setup

1. Clone the repository:

   git clone https://github.com/aniketk17/Pbl-2.git
   
   

2. Create Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install Dependencies:

   pip install -r requirements.txt
   

4. Apply Database migrations:

   python manage.py migrate
   python manage.py makemigrations
   

5. Create a superuser to access the admin dashboard:

   python manage.py createsuperuser
   

6. Start the development server:

   python manage.py runserver