Title: AI-102関連合格問題、AI-102試験内容 [Print This Page] Author: edlong991 Time: 3 hour before Title: AI-102関連合格問題、AI-102試験内容 P.S.Xhs1991がGoogle Driveで共有している無料の2026 Microsoft AI-102ダンプ：https://drive.google.com/open?id=1rPDZsVL-lZD93E16fs0FOROi407xGx6b
Xhs1991というサイトには全的な資源とMicrosoftのAI-102の試験問題があります。それに、MicrosoftのAI-102の試験の実践経験やテストダンプにも含まれています。Xhs1991は受験生たちを助けて試験の準備をして、試験に合格するサイトですから、受験生のトレーニングにいろいろな便利を差し上げます。あなたは一部の試用問題と解答を無料にダウンロードすることができます。Xhs1991のMicrosoftのAI-102の試験中に絶対な方法で転送することでなく、Xhs1991は真実かつ全面的な試験問題と解答を提供していますから、当社がオンラインするユニークなのMicrosoftのAI-102の試験トレーニング資料を利用したら、あなたが気楽に試験に合格することができるようになります。Xhs1991は合格率が１００パーセントということを保証します。
Microsoft AI-102試験は、AzureプラットフォームでAIソリューションを設計および実装する際の専門知識を実証するのに役立つ、やりがいのあるがやりがいのある認証です。キャリアを前進させたり、スキルを向上させたり、最新のテクノロジーを最新の状態に保ちたりする場合でも、この試験は競争力のあるAI雇用市場で能力を紹介し、目立つ能力を紹介する優れた方法です。
Microsoft AI-102認定試験は、Microsoft Azureプラットフォーム上でAIソリューションを設計および実装する能力を証明するための貴重な資格です。AIと機械学習のコンセプトに強い理解力と、実世界のプロジェクトでの実践的な経験を持つことで、候補者は自信を持って試験に備えることができます。
AI-102試験内容、AI-102日本語学習内容弊社はAI-102問題集を買ったお客様が試験に成功することを保証いたします。もしお客様は安心できないなら、弊社は無料のAI-102サンプルを提供いたしますから、お客様は弊社のウェブでサンプルを無料でダウンロードできて、お客様の要求にふさわしいということを確認してから、弊社のAI-102問題集を選ぶことができます。 Microsoft Designing and Implementing a Microsoft Azure AI Solution 認定 AI-102 試験問題 (Q367-Q372):質問 # 367
You are developing the knowledgebase.
You use Azure Video Analyzer for Media (previously Video indexer) to obtain transcripts of webinars.
You need to ensure that the solution meets the knowledgebase requirements.
What should you do?
A. Enable multi-language detection for videos
B. Configure audio indexing for videos only
C. Build a custom Person model for webinar presenters
D. Create a custom language model
正解：D
解説：
Can search content in different formats, including video
Audio and video insights (multi-channels). When indexing by one channel, partial result for those models will be available.
Keywords extraction: Extracts keywords from speech and visual text.
Named entities extraction: Extracts brands, locations, and people from speech and visual text via natural language processing (NLP).
Topic inference: Makes inference of main topics from transcripts. The 2nd-level IPTC taxonomy is included.
Artifacts: Extracts rich set of "next level of details" artifacts for each of the models.
Sentiment analysis: Identifies positive, negative, and neutral sentiments from speech and visual text.
Reference: https://docs.microsoft.com/en-us ... eo-indexer-overview
質問 # 368
You need to create a visualization of running sales totals per quarter as shown in the following exhibit.
What should you create in Cower Bl Desktop;1
A. a bar chart
B. a ribbon chart
C. a decomposition tree
D. a waterfall chart
正解：A
質問 # 369
You need to upload speech samples to a Speech Studio project. How should you upload the samples?
A. Upload individual audio files in the FLAC format and manually upload a corresponding transcript in Microsoft Word format.
B. Combine the speech samples into a single audio file in the .wma format and upload the file.
C. Upload a .zip file that contains a collection of audio files in the .wav format and a corresponding text transcript file.
D. Upload individual audio files in the .wma format.
正解：C
解説：
Explanation
To upload your data, navigate to the Speech Studio . From the portal, click Upload data to launch the wizard and create your first dataset. You'll be asked to select a speech data type for your dataset, before allowing you to upload your data.
The default audio streaming format is WAV
Use this table to ensure that your audio files are formatted correctly for use with Custom Speech:
Reference: https://docs.microsoft.com/en-us ... eech-test-and-train
質問 # 370
You have a custom Azure OpenAI model.
You have the files shown in the following table.
You need to prepare training data for the model by using the OpenAI CLI data preparation tool. Which files can you upload to the tool?
A. File2.xml only
B. File3.pdf only
C. File1.tsv and File4.xslx only
D. Filel.tsv only
E. File1.tsv, File2.xml, Fil3.pdf and File4.xslx
F. File1.tsv.File2.xml and File4.xslx only
G. File4.xlsx only
正解：D
解説：
You need to prepare training data for Azure OpenAI custom model fine-tuning using the OpenAI CLI data preparation tool.
* Supported input formats: JSONL (primary).
* CLI pre-processing accepted formats: TSV, CSV, JSON.
* Not supported: PDF, XML, XLSX directly.
Checking files:
* File1.tsv (80 MB) # Supported (CLI can convert TSV to JSONL).
* File2.xml (25 MB) # Not supported (XML not accepted).
* File3.pdf (50 MB) # Not supported.
* File4.xlsx (200 MB) # Not supported directly.
The answer: A. File1.tsv only
質問 # 371
You plan to use a Language Understanding application named app1 that is deployed to a container.
App1 was developed by using a Language Understanding authoring resource named lu1.
App1 has the versions shown in the following table.
You need to create a container that uses the latest deployable version of app1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. (Choose three.) 正解：
解説：
Reference: https://docs.microsoft.com/en-us ... uis-container-howto
