Cloud Technologies
News Mood App
The News Mood App is a serverless AI-powered application that retrieves news articles, performs sentiment analysis using Amazon Comprehend, and stores categorized results in Amazon DynamoDB. Users can request news articles filtered by sentiment (positive, neutral, or negative) via an API Gateway. This project demonstrates AWS Lambda's capabilities in managing real-time data and leveraging AI for text analysis.
My Role
Cloud Solutions Architect
Duration
1 year
Tools
AWS Lambda, Amazon DynamoDB, Amazon API Gateway, Amazon Comprehend, AWS CloudWatch, Python, News API
Link
Overview
Real-Time News Retrieval – Ensuring timely and accurate news updates while integrating an external API.
Sentiment Analysis Accuracy – Analyzing and categorizing sentiment effectively using AI while avoiding misclassification.
Scalable Storage & Retrieval – Storing large volumes of news data efficiently and enabling fast sentiment-based queries.
Latency & Performance Optimization – Minimizing response time for API queries and ensuring smooth user experience.
Integrated News API – Connected the application with newsapi.org for real-time news retrieval.
Leveraged Amazon Comprehend – Utilized AWS's NLP service for accurate sentiment detection and categorization.
Optimized DynamoDB Schema – Designed an efficient, indexed data structure to store news articles and enable fast sentiment-based lookups.
Implemented CloudWatch Monitoring – Used AWS CloudWatch logs to track API performance and optimize Lambda execution time.
