Microsoft AI School - Processing Text Using AI

Introduction

Applications require large volumes of data which are majorly in text format. Azure Cognitive services allow you to create applications that can extract semantic meaning from unstructured text and translate them between different languages. 

The following learning path in Microsoft AI School will help you to learn numerous techniques to process text using Azure cognitive services like Text Analytics and Translator: “Process and translate text with Azure Cognitive Services.” This learning path has two modules. Read ahead to get a quick peek at each module of this learning path. 

Prerequisites

Before proceeding with this learning path, you should fulfill the following prerequisites:

• You should be familiar with Microsoft Azure and must be able to navigate the Azure portal.
• You should have a minimal experience in programming with C# or Python.

Module 1: Extract Insights From Text With The Text Analytics Service

Humans rely on their experiences and knowledge to gain insights into the text. However, an AI application must be provided with prior knowledge so that it can gain insights and analyze unstructured text. Often it’s a complex task to program such techniques. and this is where the Text Analytics cognitive service comes to your rescue, allowing you to program models with the help of pre-trained models. The Text Analytics Azure Cognitive Service facilitates you with an API for common text analysis techniques that can be easily integrated into your application code.

Text Analytics is a text-mining AI service in Microsoft Azure that extracts semantic insights from texts (also known as sentiment analysis) that enables you to create intelligent apps and services.

Some classic use cases and features of Text Analytics are:

• Entity Extraction enables applications to gain essential insights into the text, including key phrases and named entities like events, organizations, and people.
• Sentiment Analysis that enables applications to identify customers' reaction towards your products and brand by analyzing their sentiments around specific topics through a technique known as opinion mining.
• Question Answering - It allows you to extract answers from content, including FAQs, blogs, manuals, and policies.
• Processing Medical Text

Thus, in the first module of this learning path, you will learn how the Text Analytics Azure Cognitive Service can be used for:

• Language Detection 
• Extracting key-phrases
• Sentiment Analysis
• Entity Extraction
• Extraction of linked entities

Here’s an overview of the units covered in this module: 

Module 2: Translate Text with The Translator Service

There are numerous languages spoken across the globe and the exchange of information between different languages is extremely important for global solutions. This brings Azure’s Translator service into the picture. 

The Translator Azure Cognitive Service is an intelligent AI service that allows you to create applications that have the ability to translate text from one language to another. 

The Translator service features an API that has support for 90 languages which can be used for:

• Language detection
• Language Translation (one-to-many)
• Script transliteration ( the process of translating a script in one language to a script in another language.)

The major features and advantages of the Translator service are:

• Broad Language Coverage - It has support for text translation in as many as 90 languages.
• Customizable Translations - This allows you to build and define custom models that can handle domain-specific terminologies.
• It provides a production-ready technology that can efficiently manage billions of translations between Microsoft products on a daily basis.
• Built-in Security - It ensures the privacy of your data as your text inputs do not get logged at the time of translation. 

Thus, in the second module of this learning path, you will learn:

• How to provision a Translator resource in Azure.
• Understand how language detection, translation and transliteration works.
• How to specify translation options.
• How to define custom translations.

Here’s an overview of the units covered in this module: 

Conclusion

Thus, if you want to learn the usage of Azure Cognitive Services to process and translate text, then this learning path will serve as the perfect guide for your learning expeditions. It will not only educate you about the numerous techniques of text processing and basic concepts but also guide you with the help of real-time examples and exercises for your practice. Another advantage of learning to use the Text cognitive services in Azure is that you require minimal programming knowledge as most of the services have predefined models that can be used without the requirement of complex coding.

Please feel free to dive into this learning path at the following link:- https://docs.microsoft.com/en-us/learn/paths/process-translate-text-azure-cognitive-services/