Microsoft AI-102 Exam With Confidence Using Practice Dumps

C: Analyze Receipt - Get Analyze Receipt Result.

Query the status and retrieve the result of an Analyze Receipt operation.

Request URL:

E: POST {Endpoint}/vision/v3.2/read/analyze

Use this interface to get the result of a Read operation, employing the state-of-the-art Optical Character Recognition (OCR) algorithms optimized for text-heavy documents.

Scenario: Contoso plans to develop a document processing workflow to extract information automatically from PDFs and images of financial documents

The document processing solution must be able to process standardized financial documents that have the following characteristics:

- Contain fewer than 20 pages.

- Be formatted as PDF or JPEG files.

- Have a distinct standard for each office.

*The document processing solution must be able to extract tables and text from the financial documents.

The document processing solution must be able to extract information from receipt images.

In the Azure AI Translator .NET SDK (Azure.AI.Translation.Text), the TextTranslationClient exposes TranslateAsync overloads that accept a target language (e.g., "fr") and an input string to translate. The call returns a Response>. Each TranslatedTextItem includes the automatically detected source language (DetectedLanguage.Language) and a collection of translations in Translations. To print the translated text for the first target language, read translation.Translations[0].Text.

Therefore:

Use TranslateAsync(targetLanguage, input) to perform the translation.

Output translation.Translations[0].Text to display the translated result.

Microsoft References

TextTranslationClient.TranslateAsync method (overloads, usage). Microsoft Learn

TextTranslationClient class overview. Microsoft Learn

TranslatedTextItem model and Translations property (array of translation results).

Quickstart: Translator text client libraries (end-to-end usage pattern). Microsoft Learn

To quickly prototype harmful-content detection (e.g., discriminatory language) with minimal development, you should provision an Azure AI Content Safety resource in the Azure portal and then try it in Content Safety Studio using “Moderate text content.” Content Safety Studio lets you test text moderation, tune thresholds, and export sample code without writing much code up front. Creating an Azure OpenAI resource or using “Protected material detection for text” isn’t required for abusive/hate moderation; “protected material” targets copyrighted/credential leakage scenarios, not general toxicity.

Microsoft References:

Quickstart: Analyze text content (use Moderate text content in the studio; prerequisite is to create a Content Safety resource). Microsoft Learn

Azure AI Content Safety overview