GitHub topics: amazon-comprehend
Ditectrev/Amazon-Web-Services-Certified-AWS-Certified-Machine-Learning-MLS-C01-Practice-Tests-Exams-Question
β³οΈ PASS: Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) by learning based on our Questions & Answers (Q&A) Practice Tests Exams.
Size: 6.88 MB - Last synced at: 12 days ago - Pushed at: 6 months ago - Stars: 59 - Forks: 38
aws-solutions/content-localization-on-aws
Automatically generate multi-language subtitles using AWS AI/ML services. Machine generated subtitles can be edited to improve accuracy and downstream tracks will automatically be regenerated based on the edits. Built on Media Insights Engine (https://github.com/awslabs/aws-media-insights-engine)
Language: Vue - Size: 60.8 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 42 - Forks: 17
hervenivon/aws-experiments-comprehend-custom-classifier
How to train a custom NLP classifier with AWS Comprehend?
Language: Jupyter Notebook - Size: 12.9 MB - Last synced at: 4 days ago - Pushed at: over 4 years ago - Stars: 28 - Forks: 12
ASUCICREPO/multilingual-contact-center
A multilingual contact center solution built with React and AWS services (Connect, Transcribe, Translate, Polly) that provides real-time translation between agents and customers speaking different languages, breaking down communication barriers in call centers.
Language: JavaScript - Size: 0 Bytes - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
ShotaroMatsuya/football-journalism
Our first Challenges of building AI-Powered APP
Language: Vue - Size: 28.6 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 0 - Forks: 0
harrybanda/QuickSeek
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.
Language: Python - Size: 5.87 MB - Last synced at: 12 days ago - Pushed at: over 2 years ago - Stars: 26 - Forks: 4
chandler767/Good-News-Machine
A web-app that aggregates a feed of positive news.
Language: JavaScript - Size: 5.08 MB - Last synced at: 14 days ago - Pushed at: almost 5 years ago - Stars: 21 - Forks: 2
danilop/serverless-positive-chat
An inclusive chat that avoids negative messages and translates the content in the language that you choose, tracking the main topics of a chat room.
Language: JavaScript - Size: 34.2 KB - Last synced at: 15 days ago - Pushed at: about 5 years ago - Stars: 54 - Forks: 5
HsiehShuJeng/cdk-comprehend-s3olap
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.
Language: TypeScript - Size: 3.43 MB - Last synced at: about 23 hours ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0
r-40021/easy-chat π¦
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Language: Svelte - Size: 809 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
aws-samples/cloud-experiments π¦
Open innovation with 60 minute cloud experiments on AWS
Language: Jupyter Notebook - Size: 22.8 MB - Last synced at: 5 months ago - Pushed at: 12 months ago - Stars: 88 - Forks: 56
NovatecConsulting/intelligent-process-automation-showcase
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/
Language: Python - Size: 9.85 MB - Last synced at: 19 days ago - Pushed at: over 1 year ago - Stars: 6 - Forks: 4
chandler767/Read-The-Room
This demo processes conversations in real-time with the Amazon Comprehend natural language processing (NLP) service to gain insights about what was said.
Language: Go - Size: 335 KB - Last synced at: 11 days ago - Pushed at: almost 5 years ago - Stars: 7 - Forks: 1
prashantverma4747/Comprehend-Sentiment-Analysis-AWS
Sentiment analysis using BOTO3 for Python on Amazon Comprehend
Language: Jupyter Notebook - Size: 8.79 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
vbudilov/website-scraper-with-amazon-comprehend
Get additional insights from your data by running it through Amazon Comprehend
Language: Kotlin - Size: 61.5 KB - Last synced at: 11 months ago - Pushed at: over 6 years ago - Stars: 13 - Forks: 5
naman884/AWS-AI-Services-Implementation
This repository contains the implementation of various AWS AI Services.
Language: Python - Size: 6.84 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
aws-solutions/document-understanding-solution π¦
Example of integrating & using Amazon Textract, Amazon Comprehend, Amazon Comprehend Medical, Amazon Kendra to automate the processing of documents for use cases such as enterprise search and discovery, control and compliance, and general business process workflow.
Language: JavaScript - Size: 132 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 228 - Forks: 91
dataiku/dss-plugin-amazon-comprehend-nlp-medical
Dataiku DSS plugin to use the Amazon Comprehend Medical API π©Ί
Language: Python - Size: 58.6 KB - Last synced at: 9 months ago - Pushed at: 12 months ago - Stars: 2 - Forks: 0
aws-samples/document-processing-pipeline-for-regulated-industries
A boilerplate solution for processing image and PDF documents for regulated industries, with lineage and pipeline operations metadata services.
Language: Python - Size: 11.4 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 50 - Forks: 12
dataiku/dss-plugin-amazon-comprehend-nlp
Dataiku DSS plugin to use the Amazon Comprehend APIs π
Language: Python - Size: 146 KB - Last synced at: 9 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0
aws-samples/aws-video-metadata-knowledge-graph-workshop
This repository contains a series of 4 jupyter notebooks demonstrating how AWS AI Services like Amazon Rekognition, Amazon Transcribe and Amazon Comprehend can help you extract valuable metadata from your video assets and store that information in a Graph database like Amazon Neptune for maximum query performance and flexibility.
Language: Jupyter Notebook - Size: 4.27 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 1
aws-samples/amazon-textract-comprehend-stepfunctions-example
A sample guide to building a serverless document processing application that can make intelligent flow-control decisions after classifying the input document type.
Language: Java - Size: 223 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 6 - Forks: 3
aws-samples/transcribe-comprehend-quicksight-demo
Sample audio transcription and analysis pipeline using Amazon Transcribe, Amazon Comprehend.
Language: Scala - Size: 148 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 4
Ryanjlowe/unofficial-office-hours-skill
Live Streamed Alexa Skill development to create a searchable index of the Alexa Office Hours Archives
Language: Python - Size: 3.01 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0
leo-capvano/sentiment_analysis_benchmarking
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.
Language: Python - Size: 3.33 MB - Last synced at: 12 months ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0
swx0/reddit-sentiment-analysis-with-AWS
Analyse user sentiments and identify entities on subreddits using AWS serverless architecture.
Language: Python - Size: 51.8 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0
Develop-Packt/Topic-Modeling-and-Theme-Extraction
In this module you will learn how to analyze topic modeling output from Amazon Comprehend, then perform topic modeling on two documents with a known topic structure.
Language: Jupyter Notebook - Size: 1.9 MB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 1 - Forks: 2
k-hasan-19/sigv4-aws
Example php scripts making sigv4 signed aws api requests
Language: PHP - Size: 10.7 KB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0
brusic/elasticsearch-ingest-aws-comprehend
Elasticsearch ingest processors using Amazon Comprehend for NLP analysis
Language: Java - Size: 25.4 KB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 7 - Forks: 2
uchimanajet7/go-reacjilator
Translate Slack message with flag emoji(e.g. :jp: :us: :uk:) reaction. :smile: Use only AWS Products(AWS Lambda functions in Go, Amazon Comprehend, Amazon Translate)
Language: Go - Size: 14.6 KB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 3 - Forks: 0
Develop-Packt/Introduction-to-Computer-Vision-and-Image-Processing
This chapter covers the Amazon Rekognition service for analyzing the content of the images using various techniques. You will learn how to analyze faces and recognize celebrities in images. You will also be able to compare faces in different images to see how closely they match with each other.
Size: 12.4 MB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 2
Develop-Packt/Using-Speech-with-the-Chatbot
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
Language: Python - Size: 2.93 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 1
Develop-Packt/Introduction-to-Conversational-Artificial-Intelligence
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
Language: Python - Size: 4.88 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 1
Develop-Packt/Analyzing-Documents-and-Text-with-Natural-Language-Processing
In this module you will look at AWS AI services and examine an emerging computing paradigm β the Serverless Computing. We will then proceed to applying NLP and the Amazon Comprehend service to analyze documents.
Language: Jupyter Notebook - Size: 886 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 1
ErnestoHkirk/TweetSentimentAnalysis
Program to analyze tweet sentiment
Language: Python - Size: 49.8 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 0
solvimm/glue-comprehend
Scaling sentiment analysis with AWS Glue and Amazon Comprehend.
Language: Python - Size: 12.7 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0
knilssen/Founding_Fathers
Provides a reliable political feed for readers to become knowledgeable and informed voters on the state political level.
Language: Python - Size: 334 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 1
