E-Commerce Website for 1618 Office Solutions

This is an E-Commerce Website with Sales Prediction using GRU-Based Neural Networks powered by Brain.js. The platform enables customers to purchase office hardware, furniture, and supplies from 1618 Office Warehouse, featuring secure checkout options.

Features

• User registration and login with role-based access (customer/admin)
• Product catalog with advanced filters (category, brand, price, etc.)
• Email notifications for order confirmation and updates using Nodemailer
• Admin dashboard for product, customer, and order management
• Real-time product availability
• Sales and customer analytics with predictive insights using historical sales data
• Bulk order support for office supplies
• Wishlist functionality for saving preferred products

Tech Stack

• Frontend:
  • React 19
  • Shadcn/UI components for modern UI
  • Tailwind CSS for styling
  • React Router for navigation
  • Recharts for data visualization
• Backend:
  • Node.js with Express.js
  • GRU-based sales prediction using Brain.js for historical sales analysis and next-sequence forecasting
  • RESTful API architecture
  • Nodemailer for email notifications
  • Heroku Postgres for database hosting
  • Heroku Scheduler for automated tasks
  • Cloudinary for image management
• Database:
  • PostgreSQL

Setup

Prerequisites

• Node.js (v14 or higher)
• npm
• Backend server running (refer to the backend setup guide)

Installation

1. Clone the repository:

   git clone <repository-url>
   cd e-commerce-sales-prediction-frontend

2. Install dependencies:

   npm install

3. Create a .env file in the root directory and configure the following environment variables:

   VITE_API_URL=youripaddress

4. Start the development server:

   npm start

5. Open your browser and navigate to http://localhost:3000.

Build for Production

To build the project for production, run:

npm run build

The production-ready files will be available in the build/ directory.

Deployment

1. Deploy the build/ directory to a static hosting service like Netlify, Vercel, or AWS S3.
2. Ensure the backend API is accessible from the deployed frontend.

Backend Repository

The backend for this project is available at:
https://github.com/batdimoiprint/e-commerce-sales-prediction-backend

License

This project is licensed under the MIT License. See the LICENSE file for details.