https://github.com/bilalm04/mail-guard

A React.js application for classifying emails as spam or not spam, styled with CSS and interfacing with a Flask-based backend API for a machine learning model.
https://github.com/bilalm04/mail-guard

css frontend github-pages machine-learning nlp nodejs reactjs

Last synced: 3 months ago
JSON representation

A React.js application for classifying emails as spam or not spam, styled with CSS and interfacing with a Flask-based backend API for a machine learning model.

• Host: GitHub
• URL: https://github.com/bilalm04/mail-guard
• Owner: BilalM04
• Created: 2024-08-29T04:32:55.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-09-11T01:40:17.000Z (4 months ago)
• Last Synced: 2024-10-11T05:41:26.797Z (3 months ago)
• Topics: css, frontend, github-pages, machine-learning, nlp, nodejs, reactjs
• Language: JavaScript
• Homepage: https://bilalm04.github.io/mail-guard/
• Size: 344 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# MailGuard

This repository contains the front-end application for classifying emails as spam or not using a machine learning model. The application is built using Node.js, React.js, and CSS, providing a user-friendly interface to interact with the email classification API. You can explore the website yourself [here](https://bilalm04.github.io/mail-guard/).



![](https://github.com/user-attachments/assets/53783afc-4171-49d5-9997-0273e360ac71)

![](https://github.com/user-attachments/assets/1cd50490-0447-423f-bd7e-b6fd8ec986ea)

  



## Features

- **Email Classification**: Users can input an email message and determine whether it is classified as spam or not.

- **Simple UI**: Clean and responsive user interface designed with React.js and CSS.

- **API Integration**: Connects to a Flask-based backend API that hosts the machine learning model. 

## Technologies Used

- **React.js**: For building the user interface.

- **Node.js**: For managing the development environment.

- **CSS**: For styling the application.

## Getting Started

### Prerequisites

- **Node.js**: Ensure you have Node.js installed on your machine. You can download it from [Node.js official website](https://nodejs.org/).

### Installation

1. **Clone the Repository**:

   ```bash

   git clone https://github.com/BilalM04/mail-guard.git

   cd mail-guard

   ```

2. **Install Dependencies:**

   ```bash

   npm install

   ```

3. **Run the Application:**

   ```bash

   npm start

   ```

4. The application will be accessible at .

## Backend

This project relies on a separate backend repository that contains the Flask API and the machine learning model for email classification. You can find the backend repository here: [Email Spam Classifier](https://github.com/BilalM04/email-spam-classifier).

## Demo

Explore the live demo: [MailGuard](https://bilalm04.github.io/mail-guard/)