The easiest way to create NLP Solution with Azure AI Language

When you want to create a solution that uses natural language processing (NLP), you can use a lot of open-source libraries. However, if you take a closer look at the Azure AI, they have NLP features through Azure AI language, and it starts from FREE.

 

Natural Language Processing (NLP) development with Azure AI involves utilizing Microsoft's suite of tools and services to build, deploy, and manage NLP models and applications. Azure offers a range of NLP-related services such as Azure Cognitive Services, Azure Machine Learning, and Azure Databricks, which provide capabilities for language understanding, sentiment analysis, named entity recognition, and more.

 

Using Azure AI for NLP development allows developers to harness the power of pre-built models and APIs for common NLP tasks, as well as the flexibility to build custom NLP models using machine learning frameworks like TensorFlow and PyTorch on Azure Machine Learning. Additionally, Azure provides infrastructure and tools for data processing, model training, and deployment, making it a comprehensive platform for NLP development.

 

By leveraging Azure AI for NLP development, businesses and developers can expedite the creation of language-aware applications, automate text analysis workflows, and gain insights from unstructured data sources. Azure's robust security and compliance features also ensure that NLP applications built on the platform adhere to industry standards and best practices. Overall, Azure AI empowers developers to create sophisticated NLP solutions while benefiting from the scalability, reliability, and performance of the Azure cloud platform.

To create an Azure AI Language project using Visual Studio, follow these steps:

 

Provision Azure Resources:

  • Create an Azure Subscription (you can create one for free).
  • Log into Language Studio.
  • If it’s your first time logging in, choose a language resource and select “Create a new language resource.” Provide details such as name, location, and resource group.
  • Use Language Studio with Your Own Text:
  • Once you’re ready to use Language Studio features on your text data, you’ll need an Azure AI-language resource for authentication and billing. I recommend you do not need to activate this because it needs to be paid, but of course, I recommend you to subscribe when the transaction goes up.
  • Follow the setup process to create your resource.
  • You can then call REST APIs and use client libraries programmatically. You can see a lot examples here Language Studio - Microsoft Azure
  • Remember to choose a location for your Azure AI language resources so the latency of the resources

 

Some NLP scenarios that you can expect:

  • Extract information that comes from the document/text. For example, you want to understand the main topic or contribution of an article
  • Classify text for sentiment analysis, language detection, and custom text classification. For example, you want to moderate content in the forum
  • Question and answer. For example, creating a Bot for simple question-and-answer.
  • Summarize information. For example, you want to create meeting notes based on the meeting documents / conversational text
  • Customize translation. For example, you want to create a translation of a natural language to cat language :D

 

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