Stock Price Prediction Model with Full-Stack Web Application and
Mohammed Abdul Moiz
Designed and developed a scalable web application using React.js forthe frontend and Node.js for the backend.
Implemented serverless architecture using AWS Lambda and API
Gateway for efficient resource utilization.
Utilized AWS DynamoDB for NoSQL data storage of stock data andpredictions.
Implemented real-time features using AWS AppSync and GraphQL
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Posted Jul 20, 2024
Built a scalable stock price prediction web app using React.js frontend and Node.js backend. Leveraged AWS for serverless architecture.
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