Natural Language Processing in Microsoft Azure- Text Analytics
Notes from my learning journey in Coursera inspired from Coach (GenAI tool)
Microsoft Azure provides a range of tools and services that can be used for natural language processing (NLP) workloads. Here are some ways you can leverage Microsoft Azure for NLP:
- Text Analytics: Azure Text Analytics service allows you to extract insights from unstructured text data. You can perform sentiment analysis, key phrase extraction, language detection, and entity recognition using this service.
- Translation: Azure Translator Text API enables you to translate text between different languages. It supports both single-word translation and full document translation.
- Language Understanding: Azure Language Understanding (LUIS) service helps you build custom language models to understand user intents and extract relevant information from user queries. It uses machine learning algorithms to improve accuracy over time.
- Speech Recognition: Azure Speech to Text service converts spoken language into written text. It can be used for transcription, voice commands, and voice-controlled applications.
- Speech Synthesis: Azure Text to Speech service converts written text into natural-sounding speech. It supports multiple languages and voices.
- Custom Models: Azure Cognitive Services allows you to train and deploy custom machine learning models for specific NLP tasks. You can use Azure Machine Learning service to build and deploy your own models.
- By utilizing these tools and services, you can develop powerful NLP applications that can analyze, understand, and generate human-like language.
The course is offered by Microsoft as part of their Azure AI services.
The course covers various modules, including Text and Speech Processing with Azure AI Services, Work with Language in Azure AI, and Explore Conversational AI. It focuses on using Azure’s text analytics service for advanced natural language processing tasks.
To use the text analytics service, you need to provision an appropriate resource in your Azure subscription.
The service can detect the language of a given text, provide sentiment analysis to determine positive or negative sentiment, extract key phrases to identify main talking points, and recognize entities mentioned in the text.
The service can be used in various industries, such as analyzing customer feedback, medical records, financial data, and research papers.
The course is designed to empower learners to leverage natural language processing capabilities in Azure to gain insights, automate tasks, and make informed decisions.
For live demo about those services check my Youtube channel AI4Innovation
#NLP #MicrosoftAzure #data science #machinelearning #artificialintelligence
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