This repository contains the implementation of various AWS AI Services.

Example php scripts making sigv4 signed aws api requests

Dataiku DSS plugin to use the Amazon Comprehend Medical API 🩺

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

Scaling sentiment analysis with AWS Glue and Amazon Comprehend.

Sentiment analysis using BOTO3 for Python on 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

Translate Slack message with flag emoji(e.g. 🇯🇵 🇺🇸 🇬🇧) reaction. 😄 Use only AWS Products(AWS Lambda functions in Go, Amazon Comprehend, Amazon Translate)

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.

チャット返信文作成支援ツール

Our first Challenges of building AI-Powered APP

Final Project - Evolution of Banking vs Evolution of Blockchain Based Finance

This construct creates the foundation for developers to explore the combination of Amazon S3 Object Lambda and Amazon Comprehend for PII scenarios and it is designed with flexibility, i.e, the developers could tweak arguments via CDK to see how AWS services work and behave.

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 demo processes conversations in real-time with the Amazon Comprehend natural language processing (NLP) service to gain insights about what was said.

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