P.S. Fast2test在Google Drive上分享了免費的、最新的AI-900考試題庫：https://drive.google.com/open?id=17_OYhdRvLUHiBW8qtyRCG8OU1uQacPrv
Microsoft的AI-900考試其實是一個技術專家考試， Microsoft的AI-900考試可以幫助和促進IT人員有一個優秀的IT職業生涯，有了好的職業生涯，當然你就可以為國家甚至企業創造源源不斷的利益，從而去促進國家經濟發展，如果所有的IT人員都這樣，那麼民富則國強。我們Fast2test Microsoft的AI-900考試培訓資料可以幫助IT人員達到這一目的，保證100%獲得認證，如果需要思考，還不如果斷的做出決定，選擇我們Fast2test Microsoft的AI-900考試培訓資料。
Microsoft AI-900考試旨在針對沒有AI技術背景但想了解更多信息的個人。該考試適合有興趣了解AI概念以及如何在Azure實施的開發人員，數據分析師，業務分析師和IT專業人員。成功完成考試後，候選人將獲得Microsoft Azure AI基礎認證的授予，該認證證明了他們對AI概念的理解以及如何在雲計算環境中應用。
“如果放棄了，那比賽同時也就結束了。”這是來自安西教練的一句大家都熟知的名言。比賽是這樣，同樣考試也是這樣的。有很多人因為沒有充分的時間準備考試從而放棄了參加AI-900認證考試。但是，如果使用了好的資料，即使只有很短的時間來準備，你也完全可以以高分通過AI-900考試。不相信嗎？Fast2test的考古題就是這樣的資料。趕快試一下吧。
要通過 AI-900 考試，候選人必須展示他們對與 AI 相關的關鍵概念的理解，例如機器學習、自然語言處理和計算機視覺。他們還必須能夠識別不同類型的 AI 解決方案，並了解如何使用 Azure 服務來開發和部署它們。
AI-900 考試涵蓋了各種主題，包括人工智能的基本概念、機器學習、自然語言處理、計算機視覺和對話式人工智能。考試還評估候選人對 Azure AI 服務的理解，例如 Azure 認知服務、Azure 機器學習和 Azure Bot 服務。通過此考試，證明候選人對 AI 概念有扎實的理解，可以有效地使用 Azure AI 服務來構建智能應用程序。此外，AI-900 考試還作為更高級的 Azure AI 認證的先決條件，例如 AI-100 設計和實施 Azure AI 解決方案。
問題 #235
Your website has a chatbot to assist customers.
You need to detect when a customer is upset based on what the customer types in the chatbot.
Which type of AI workload should you use?
答案：A
解題說明：
Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing
問題 #236
Select the answer that correctly completes the sentence.
答案：
解題說明：
問題 #237
In which two scenarios can you use the Form Recognizer service? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
答案：B,D
解題說明：
The correct answers are A and D because both scenarios involve extracting structured information from documents, which is exactly what Azure Form Recognizer is designed to do.
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Explore computer vision", Form Recognizer is an Azure Cognitive Service that uses advanced Optical Character Recognition (OCR) and machine learning to extract key-value pairs, tables, and text from structured and semi-structured documents such as receipts, invoices, business cards, and forms. It allows organizations to automate data entry and digitize document processing.
* A. Extract the invoice number from an invoice # CorrectForm Recognizer can identify fields such as invoice number, total amount, date, vendor name, and billing address directly from invoices. It uses prebuilt models for invoices and receipts that automatically detect and extract relevant information without requiring extensive manual labeling. As stated in Microsoft Learn, "Form Recognizer extracts information from documents like receipts and invoices and returns structured data including key-value pairs."
* D. Identify the retailer from a receipt # CorrectThe prebuilt receipt model in Form Recognizer can read printed or scanned receipts and extract data points such as retailer name, transaction date, total amount, and tax information. This makes it ideal for expense reporting, auditing, or financial reconciliation.
The following options are incorrect:
* B. Translate a form from French to English # This task involves language translation, which is performed by Azure Translator, not Form Recognizer.
* C. Find an image of a product in a catalog # This requires object detection or image classification, which are part of Computer Vision, not Form Recognizer.
Therefore, based on Microsoft's AI-900 learning objectives and documentation, the two correct scenarios are:
# A. Extract the invoice number from an invoice
# D. Identify the retailer from a receipt
問題 #238
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.
答案：
解題說明：
Explanation:
The correct order of processes before deploying a model as a service is:
(1) Data preparation # (2) Model training # (3) Model evaluation.
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Explore the machine learning process", machine learning follows a structured lifecycle that involves several sequential stages. Before a model can be deployed, the data must be properly prepared, the model must be trained, and then its performance must be evaluated to ensure accuracy and reliability.
* Data Preparation:The first stage involves collecting, cleaning, and transforming raw data into a usable format. Azure Machine Learning provides tools like Data Wrangler, Data Labeling, and Data Transformation pipelines to ensure the dataset is accurate and consistent. As per Microsoft Learn, "data preparation is essential to remove noise, handle missing values, and split the dataset into training and testing sets." This step ensures the model learns from quality input.
* Model Training:In this step, algorithms are applied to the prepared training data to create a predictive model. The system learns patterns and relationships from the data. Azure Machine Learning allows model training using AutoML, custom code, or designer pipelines. The training process produces a model that can make predictions, but it still needs to be tested before deployment.
* Model Evaluation:Once trained, the model's performance is tested against unseen (test) data.
Evaluation metrics like accuracy, precision, recall, and F1-score are analyzed to verify if the model meets business and performance requirements. Microsoft Learn defines this stage as "assessing the model's performance to determine its readiness for deployment." After these three processes, the model can then be deployed as a web service using Azure Machine Learning endpoints. Model retraining happens later when new data becomes available, and data encryption is a security process, not part of model development steps.
問題 #239
To complete the sentence, select the appropriate option in the answer area.
答案：
解題說明：
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/linear-regression
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize-model-clustering Regression is a form of machine learning that is used to predict a numeric label based on an item's features.
https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer/introduction
問題 #240
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AI-900在線題庫: https://tw.fast2test.com/AI-900-premium-file.html
順便提一下，可以從雲存儲中下載Fast2test AI-900考試題庫的完整版：https://drive.google.com/open?id=17_OYhdRvLUHiBW8qtyRCG8OU1uQacPrv