AWS Comprehend is an event-driven, serverless data processing pipeline that leverages AWS services to perform natural language processing and analysis on user-submitted text files.

This is a project to classify customer requests based on the customer request text using AI - NLP. I have used AWS Comprehend, AWS Step Functions and Lambda Functions. In addition to these components, Zendesk supports natively connection to the AWS Event Bridge, this means that all ticket events in Zendesk are sent to AWS to process and update t…

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

Chatbot Translator App with AWS, Golang and Terraform

Team - Brogrammers. AIRA - Software Solution for Next Generation E-commerce.

Hue Speech to Sentiment Lighting System

Team - Brogrammers. SHADE Engine to detect the emotions of a person based on his/her social media activity and recommend measures to improve upon the same.

Example php scripts making sigv4 signed aws api requests

A Discord bot that replies a GIF of Pepa Madrigal from Encanto whenever it detects a negative message

Comparison of AWS Comprehend and SpaCy on a subset of the Amazon Handmade reviews for sentiment analysis and NER

Pipeline for ingesting and leveraging text data using AWS services

List of amazing AWS Services that can be utilized.🚀

Web application where users can create, answer, rate and share surveys.

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 build a serverless architecture from scratch with AWS Lambda.

SHADE Engine to detect the emotions of a person based on his/her social media activity and recommend measures to improve upon the same.

Examples working with AWS SDK via. Python Boto3 to make calls to Comprehend APIs

Audio Feedback Sentiment Analyzer with AWS Comprehend | Transcribe Exposed as a REST API

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…