A pipeline to extract and enrich data from documents
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Updated
May 24, 2024 - Python
A pipeline to extract and enrich data from documents
Simple and Distributed Machine Learning
Summarizes emails with artificial intelligence. Based on the main topic of a message, the most important information is extracted.
Code Examples used by the Quickstarts in the Cognitive Services Documentation
A repo to showcase a Form Recognizer sample
workshop materials to build intelligent solutions on Open AI
This repository showcases how to automate the process of generating synopsis in multiple languages, taglines, SEO keyword using Azure Cognitive Services and Azure OpenAI.
AI Engineer using Microsoft Azure
QuestionAnswerPortalのAPI サーバー
This sample shows how to take text documents as a input via BlobTrigger, does Text Summarization processing using the AI Congnitive Language service, and then outputs to another text document using BlobOutput binding. Uses Azure Functions Python v2 programming model.
This project is a chatbot that uses a language learning model to get context for the user’s questions, using different context services like API or Azure.
Web app that converts speech to a text transcript and lets you save the generated transcripts to OneDrive using Microsoft Graph
Text Analytics Jupyter Notebook example for the Azure cognitive service
Text Analytics Jupyter Notebook example for the Azure cognitive service
Integration of Azure Cognitive Services into your Python Flask applications
Luna is a versatile virtual assistant designed to enhance productivity and streamline daily tasks. Leveraging advanced AI and natural language processing technologies, Luna offers intuitive voice interaction, providing users with personalized assistance for various tasks.
Atividade desenvolvida sobre Azure Cognitive Search, seguindo as orientações do curso da DIO com a orientadora Valéria Baptista bem como com o passo a passo descrito no link: AI Search.
Summarise cloud news and send it to Slack
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