A boilerplate solution for processing image and PDF documents for regulated industries, with lineage and pipeline operations metadata services.

As an Intelligent Process Automation showcase. We combined Business Process Management with Artificial Intelligence, and the result was awesome! Find out more: https://www.novatec-gmbh.de/en/blog/ipa-camunda-comprehend/

QuickSeek is a chrome extension that allows you to easily search and navigate through a YouTube video, you can quickly find and watch only parts of the video that contain words you are looking for. The Chrome extension uses Amazon Transcribe to make the audio searchable and Amazon Comprehend to perform sentiment analysis on the transcript.

Program to analyze tweet sentiment

This module looks at how use Amazon Connect, Lex, and Lambda to interact with a chatbot using voice. You will create a personal call center using Amazon Connect and you will learn how to connect the call center to your Lex chatbot

This module teaches you how to design a chatbot using Amazon Lex by following the best design practices for conversational AI. You will start by learning the basics of chatbots. Then, you will use Amazon Lex to create a custom chatbot that gets the latest stock market quotes by recognizing the intent in text

Provides a reliable political feed for readers to become knowledgeable and informed voters on the state political level.

Dataiku DSS plugin to use the Amazon Comprehend APIs 📚

Live Streamed Alexa Skill development to create a searchable index of the Alexa Office Hours Archives

Dataiku DSS plugin to use the Amazon Comprehend Medical API 🩺

This repository contains the implementation of various AWS AI Services.

Scaling sentiment analysis with AWS Glue and Amazon Comprehend.

Analyse user sentiments and identify entities on subreddits using AWS serverless architecture.

Front-end website | Backend API | Authentication | Backend compute functions | Asynchronous reporting workflow | Distributed tracing | Monitoring features | Improving performance

A benchmark comparison project among the most popular sentiment analysis engines: VaderSentiment, TextBlob, Azure Text Analysis and Amazon Comprehend. The benchmarker is a python module that supports 3 datasets: IMDb, Sentiment140 and Twitter.

Amazon Comprehend sample code that calls Sentiment and Key phrase APIs and does additional processing.