22.3 aztext demo
The pre-built demonstration highlights the capabilities of the package.
ml demo aztext
Here is a sample of the interaction.
==================== Azure Text Analytics ==================== Welcome to a demo of the pre-built models for Text Analytics provided through Azure's Cognitive Services. This service extracts information from text that we supply to it, providing information such as the language, key phrases, sentiment (-1 to 1 as negative to positive), and entities. Press Enter to continue: ==================== Language Information ==================== We will first demonstrate the automated identification of language. Below are a few "documents" in different languages which are passed on to the cloud for processing using the following language API URL: Press Enter to continue: 1 Text as a sample document written in English. This is English (en) with score of 1.0. 2 Este es un document escrito en Español. This is Spanish (es) with score of 1.0. ... ================== Sentiment Analysis ================== Now we look at an analysis of the sentiment of the document/text. This is done so by passing the text of the text on to the sentiment API URL shown below for processing in the cloud. The results are returned as a number between 0 and 1 with 0 being the most negative and 1 being the most positive. Press Enter to continue: 1 I had a wonderful experience! Rooms were wonderful and staff helpful. This has a sentiment rating of 0.94. 2 I had a terrible time at the hotel. The staff was rude and food awful. This has a sentiment rating of -1.00. ... ======== Entities ======== Our final demonstration identifies the entities refered to in the text. As a bonus the API generates a link to Wikipedia for more information! As above, the text is passed on to the cloud through the API at the URL below. ...
Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0