AWS Certified AI Practitioner (AIF-C01) exam preparation

ATS Buddy is a production-ready, serverless AI resume analyzer built on AWS Bedrock (Nova Lite). It intelligently compares resumes against job descriptions, providing compatibility scores, missing keyword detection, and AI-powered resume enhancements—all while ensuring enterprise-grade PII protection and cost-efficient auto-scaling.

Analyzing Twitter in real time with Kinesis, Lambda, Comprehend and ElasticSearch

Use AWS to stream and analyze the sentiment of live tweets from Twitter based on a certain keyword.

Right call center quality assurance monitoring written in Python

Example of Amazon SageMaker Ground Truth and Amazon Comprehend Custom NER

Pipeline for ingesting and leveraging text data using AWS services

Web page that can accept English text files and run various types of nlp

Using AWS Comprehend NLP Service, Python boto3, json toolkits

A lightweight, highly configurable tool for scanning files for personally identifiable information (PII) and other sensitive data. It uses AWS Comprehend and custom regex patterns, supports fast multi-threaded execution, and can run as a standalone tool or as a GitHub Action.

Natural Language Processing Based RealTime Voicemail Routing System for Health Insurance Enterprise

Interacting with public cloud object storage

A web application that identifies all Artist's Exhibition Titles from a given CV. The text detection is handled by AWS Textract and title detection is handled by AWS Comprehend.

This project automates the extraction, summarization, and analysis of various document formats (PDF, TXT, CSV, images) without requiring manual review.

In this repository you will find an aws-sample that will create an AWS Comprehend classification model from documents. It will then use that classification model to split documents. Check out the attached blog link to learn more about this project!

This repo is developed to perform the sentiment analysis on Arabic tweets using AWS Comprehend and Arsent Dictionary based approach.

Real-time Twitter sentiment analysis using AWS services. Captures tweets, analyzes sentiment with Comprehend, and stores results in DynamoDB for visualization and insights into trends.

An sentiment bot for Slack written in Python

A serverless application which is built MS) using a multi-cloud deployment model, and backend-as-a-service (BaaS). The LMS provides customization feature and additional services for instructors, and limited services to students. The LMS provides online virtual assistance, which can quickly answer the queries of users, and in addition, it provide…

A realtime analytics stack using AWS Kinesis Firehose, Lambda, and RDS