AI-Powered E-Commerce Platform

A comprehensive e-commerce solution showcasing advanced AI/ML capabilities, modern web development, and cloud technologies.

🚀 Features

Frontend (Angular + TypeScript)

• Modern, responsive UI with Angular 17+
• Advanced product catalog with AI-powered recommendations
• Real-time search with NLP capabilities
• Computer vision integration for visual search
• Progressive Web App (PWA) features
• State management with NgRx
• Comprehensive testing suite

Backend (Node.js + Express)

• RESTful API with TypeScript
• JWT authentication and authorization
• Real-time notifications with WebSockets
• Payment processing integration
• Order management system
• Admin dashboard APIs
• Comprehensive API documentation

AI/ML Services (Python)

• Recommendation Engine: Collaborative filtering and content-based recommendations
• NLP Processing: Sentiment analysis, product categorization, search optimization
• Computer Vision: Image recognition, visual search, product similarity
• Vector Database: Feature store for ML embeddings
• Predictive Analytics: Demand forecasting, price optimization

Database Architecture

• SQL Server: User data, orders, products, transactions
• MongoDB: Product catalogs, reviews, AI features
• Vector Database: ML embeddings and feature store
• Redis: Caching and session management

Cloud Infrastructure (AWS)

• EC2 instances for scalable deployment
• RDS for SQL Server database
• S3 for file storage and CDN
• Lambda functions for serverless ML processing
• CloudFront for global content delivery
• Elastic Beanstalk for application deployment

🛠️ Technology Stack

Frontend

• Angular 17+
• TypeScript 5+
• RxJS for reactive programming
• Angular Material for UI components
• NgRx for state management
• PWA capabilities

Backend

• Node.js 18+
• Express.js with TypeScript
• JWT for authentication
• Socket.io for real-time features
• Stripe for payment processing
• AWS SDK integration

AI/ML

• Python 3.9+
• TensorFlow 2.x for deep learning
• PyTorch for advanced ML models
• scikit-learn for traditional ML
• spaCy for NLP processing
• OpenCV for computer vision
• Pinecone for vector database

Databases

• Microsoft SQL Server
• MongoDB
• Redis
• Vector Database (Pinecone)

Cloud & DevOps

• AWS (EC2, RDS, S3, Lambda, CloudFront)
• Docker containerization
• GitHub Actions for CI/CD
• Azure DevOps integration

📁 Project Structure

ecommerce-ai-platform/
├── client/                 # Angular frontend
│   ├── src/
│   │   ├── app/
│   │   │   ├── components/
│   │   │   ├── services/
│   │   │   ├── store/
│   │   │   └── models/
│   │   └── assets/
│   └── package.json
├── server/                 # Node.js backend
│   ├── src/
│   │   ├── controllers/
│   │   ├── models/
│   │   ├── routes/
│   │   ├── middleware/
│   │   └── services/
│   └── package.json
├── ml-service/            # Python ML services
│   ├── models/
│   ├── services/
│   ├── utils/
│   └── requirements.txt
├── database/              # Database schemas and migrations
├── aws/                   # Cloud infrastructure
├── docs/                  # Documentation
└── docker-compose.yml

🚀 Quick Start

Prerequisites

• Node.js 18+
• Python 3.9+
• SQL Server
• MongoDB
• Redis
• AWS Account

Installation

1. Clone and install dependencies:

git clone <repository-url>
cd ecommerce-ai-platform
npm run install-all

2. Set up environment variables:

cp .env.example .env
# Edit .env with your configuration

3. Start all services:

npm run dev

This will start:

• Angular frontend on http://localhost:4200
• Node.js backend on http://localhost:3000
• Python ML service on http://localhost:5000

🔧 Development

Frontend Development

cd client
npm start

Backend Development

cd server
npm run dev

ML Service Development

cd ml-service
python app.py

🧪 Testing

# Run all tests
npm test

# Run specific test suites
cd client && npm test
cd server && npm test

📊 AI/ML Features

Recommendation System

• Collaborative filtering based on user behavior
• Content-based recommendations using product features
• Hybrid approach combining both methods
• Real-time recommendation updates

Natural Language Processing

• Product search with semantic understanding
• Sentiment analysis of customer reviews
• Automated product categorization
• Chatbot for customer support

Computer Vision

• Visual product search
• Similar product recommendations
• Quality assessment of product images
• Automated product tagging

Predictive Analytics

• Demand forecasting for inventory management
• Price optimization based on market trends
• Customer lifetime value prediction
• Churn prediction and prevention

🌐 Deployment

AWS Deployment

# Deploy to AWS using CloudFormation
cd aws
aws cloudformation create-stack --stack-name ecommerce-ai --template-body file://template.yaml

Docker Deployment

docker-compose up -d

📈 Performance & Monitoring

• Real-time performance monitoring
• AI model performance tracking
• Database query optimization
• CDN integration for global performance
• Automated scaling based on demand

🔒 Security

• JWT-based authentication
• Role-based access control
• Data encryption at rest and in transit
• PCI DSS compliance for payment processing
• Regular security audits and updates

📚 API Documentation

• Swagger/OpenAPI documentation
• Interactive API explorer
• Postman collection for testing
• Comprehensive error handling

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new features
5. Submit a pull request

📄 License

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

🎯 Key Achievements

This project demonstrates:

• 3+ years Angular/TypeScript experience with modern architecture
• 3+ years AWS expertise with scalable cloud solutions
• 2+ years AI/ML focus with production-ready ML services
• 2+ years Python/TensorFlow/PyTorch with advanced ML implementations
• Leadership in AI projects with mentoring and innovation
• Strong communication skills through comprehensive documentation
• Database expertise with SQL Server and NoSQL solutions
• Independent development with full-stack capabilities