For which type of tasks would you use Azure Text Analytics?

Azure Text Analytics is specifically designed for tasks involving natural language processing, making it particularly useful for applications such as sentiment analysis, key phrase extraction, language detection, and named entity recognition. Sentiment analysis, for instance, allows you to assess the emotional tone behind a body of text, helping companies understand customer opinions and feedback on their products or services.

Choosing options focused on image recognition, mathematical simulations, or large-scale data processing would not align with Azure Text Analytics' capabilities. Image recognition and classification are better suited for Azure's Computer Vision services, while complex mathematical simulations would typically utilize Azure's computational resources and frameworks. Large-scale data processing might involve Azure Data Lake or Azure Data Factory rather than the Text Analytics service, which is narrowly focused on text and language-related tasks. Thus, the use of Azure Text Analytics for natural language processing tasks is the right fit in this context.