Microsoft Designing and Implementing a Microsoft Azure AI Solution Exam Practice Tests and PDFs

Box 1: Azure Blob storage At the start of the pipeline, you have unstructured text or non-text content (such as images, scanned documents, or JPEG files). Data must exist in an Azure data storage service that can be accessed by an indexer. Box 2: Computer Vision API Scenario: Provide users with the ability to search insight gained from the images, manuals, and videos associated with the products. The Computer Vision Read API is Azure's latest OCR technology (learn what's new) that extracts printed text (in several languages), handwritten text (English only), digits, and currency symbols from images and multi-page PDF documents. Box 3: Translator API Scenario: Product descriptions, transcripts, and all text must be available in English, Spanish, and Portuguese. Box 4: Azure Files Scenario: Store all raw insight data that was generated, so the data can be processed later. Incorrect Answers: The custom vision API from Microsoft Azure learns to recognize specific content in imagery and becomes smarter with training and time. Reference: https://docs.microsoft.com/en-us/azure/search/cognitive-search-concept-intro https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr

Box 1: QnA Maker Editor Scenario: Provide all employees with the ability to edit Q&As. The QnA Maker Editor (read/write) has the following permissions: Create KB API Update KB API Replace KB API Replace Alterations "Train API" [in new service model v5] Box 2: Contributor Scenario: Only senior managers must be able to publish updates. Contributor permission: All except ability to add new members to roles Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/reference-role-based-access- control

Scenario: Support autocompletion and autosuggestion based on all product name variants. A: Call a suggester-enabled query, in the form of a Suggestion request or Autocomplete request, using an API. API usage is illustrated in the following call to the Autocomplete REST API. POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2020-06-30 { "search": "minecraf", "suggesterName": "sg" } B: In Azure Cognitive Search, typeahead or "search-as-you-type" is enabled through a suggester. A suggester provides a list of fields that undergo additional tokenization, generating prefix sequences to support matches on partial terms. For example, a suggester that includes a City field with a value for "Seattle" will have prefix combinations of "sea", "seat", "seatt", and "seattl" to support typeahead. F. Use the default standard Lucene analyzer ("analyzer": null) or a language analyzer (for example, "analyzer": "en.Microsoft") on the field. Reference: https://docs.microsoft.com/en-us/azure/search/index-add-suggesters

Scenario: All videos must have transcripts that are associated to the video and included in product descriptions. Product descriptions, transcripts, and all text must be available in English, Spanish, and Portuguese. Step 1: Upload the video to blob storage Given a video or audio file, the file is first dropped into a Blob Storage. T Step 2: Index the video by using the Video Indexer API. When a video is indexed, Video Indexer produces the JSON content that contains details of the specified video insights. The insights include: transcripts, OCRs, faces, topics, blocks, etc. Step 3: Extract the transcript from the Video Indexer API. Step 4: Translate the transcript by using the Translator API. Reference: https://azure.microsoft.com/en-us/blog/get-video-insights-in-even-more-languages/ https://docs.microsoft.com/en-us/azure/media-services/video-indexer/video-indexer-output-json-v2

Box 1: api-nam.cognitive.microsofttranslator.com https://docs.microsoft.com/en-us/azure/cognitive-services/translator/reference/v3-0-reference Box 2: /translate Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/translator/reference/v3-0-translate