Match the types of natural languages processing workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Select and Place:
- Entity recognition
- Key phrase extraction
- Language modeling
- Sentiment analytics
- Natural language processing
- Speech recognition and speech synthesis
- Extracts persons, locations, and organizations from the text.
- Evaluates text along a positive-negative scale.
- Returns text translated to the specified target language.
Key phrase extraction: Extracts persons, locations, and organizations from the text.
Sentiment analysis: Evaluates text along a positive-negative scale.
Translation: Returns text translated to the specified target language.
Box 1: Key phrase extraction: Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.
Box 2: Sentiment analysis: Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Box 3: Translation:
Using Microsoft’s Translator text API
This versatile API from Microsoft can be used for the following:
Translate text from one language to another.
Transliterate text from one script to another.
Detecting language of the input text.
Find alternate translations to specific text.
Determine the sentence length.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.