🧠 Predictive Inventory & Demand Planning System

A cloud-native, end-to-end solution to forecast inventory demand using real-time sales data, AWS infrastructure, and machine learning.

🚀 Features

• Real-time data ingestion via API Gateway and AWS Lambda
• Data transformation using AWS Glue
• Forecasting with ML models trained on Amazon SageMaker
• Visual dashboards with Amazon QuickSight and React + Amplify
• CI/CD pipeline via GitHub Actions and AWS CDK

📁 Project Structure

predictive-inventory/ ├── api/ # Lambda for ingestion ├── forecast/ # Forecast Lambda & SageMaker code ├── etl/ # Glue jobs and data scripts ├── frontend/ # React + Amplify app ├── mock-data/ # Sample dataset script + CSV ├── .github/workflows/ # GitHub Actions config ├── cdk/ # AWS CDK infrastructure code ├── README.md # Project overview ├── requirements.txt # Python dependencies └── LICENSE # MIT License

🧪 Technologies Used

• AWS Lambda, API Gateway, S3, Glue, SageMaker, Step Functions, EventBridge, IAM, CDK
• Python, Pandas, Scikit-Learn, React.js, Amplify, QuickSight
• GitHub Actions for CI/CD

📜 License

MIT License