P.S. Free & New AI-901 dumps are available on Google Drive shared by ITexamReview: https://drive.google.com/open?id=1ZkBOg9FSClEDvY3Mjyc1zV-iV56n59la
For one thing, the most advanced operation system in our company which can assure you the fastest delivery speed on our AI-901 exam questions. For another thing, with the online app version of our AI-901 actual exam, you can just feel free to practice the questions in our AI-901 Training Materials on all kinds of electronic devices. In addition, under the help of our AI-901 exam questions, the pass rate among our customers has reached as high as 98% to 100%. We are look forward to become your learning partner in the near future.
| Topic | Details |
|---|---|
| Topic 1 |
|
| Topic 2 |
|
>> Latest AI-901 Braindumps Questions <<
Unlike those impotent practice materials, our AI-901 study questions have salient advantages that you cannot ignore. They are abundant and effective enough to supply your needs of the AI-901 exam. Since we have the same ultimate goals, which is successfully pass the AI-901 Exam. So during your formative process of preparation, we are willing be your side all the time. As long as you have questions on the AI-901 learning braindumps, just contact us!
NEW QUESTION # 111
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: In the new Microsoft Foundry portal, you must fine-tune a model before you can deploy the model. = No Fine-tuning is optional. Microsoft's Foundry model deployment documentation describes deploying Foundry Models directly from the model catalog for inference. It does not require fine-tuning first.
Statement 2: In the new Microsoft Foundry portal, you can test a model from the model catalog only after you deploy the model. = No Microsoft documentation states that some Foundry Tools are available to try via the model catalog without a project, and Foundry playgrounds are used for prototyping and validation before production. Therefore, the statement using "only after you deploy" is too restrictive.
Statement 3: In the new Microsoft Foundry portal, you can deploy a model from the model catalog only after retraining the model. = No Retraining/fine-tuning is not required before deployment. Microsoft states that after you deploy a Foundry Model, you can interact with it in the Foundry Playground and use it from code, and the deployment workflow starts by selecting a model from the model catalog and choosing Deploy.
NEW QUESTION # 112
You are developing a web app that processes invoices to calculate expenses.
You need to extract structured fields, including nested values, from the invoices by using a defined schema.
What should you use?
Answer: B
Explanation:
The requirement is to extract structured fields, including nested values, from invoices by using a defined schema. In Azure Content Understanding, an analyzer is the processing unit that defines how content is analyzed, what information is extracted, and how the output is structured, including JSON fields.
Microsoft's Content Understanding document solutions documentation states that Content Understanding uses customizable analyzers to extract essential information, fields, and relationships from documents and forms. Microsoft's quickstart also shows invoice processing with the prebuilt- invoice analyzer to extract structured data from an invoice document.
NEW QUESTION # 113
You are reviewing best practices for using AI at your company.
Which Microsoft responsible AI principle is each task an example of? To answer, drag the appropriate principles to the correct tasks. Each task may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation:
* Fairness
* Privacy and security
* Transparency
* Reliability and safety
Comprehensive and Detailed Explanation with all Azure AI documents : =
Evaluating model outputs to ensure that decisions are NOT biased against specific demographic groups:
Fairness
Microsoft's responsible AI principle of fairness means AI systems should treat people fairly and avoid unfair bias across demographic groups.
Encrypting sensitive customer data and restricting system access to authorized personnel: Privacy and security The privacy and security principle requires AI systems to protect personal and sensitive data and prevent unauthorized access.
Informing users when they are interacting with an AI system and explaining the system's capabilities and limitations: Transparency The transparency principle requires that people understand when they are interacting with AI and understand the system's purpose, capabilities, and limitations.
Testing AI systems under different conditions to reduce unexpected failures: Reliability and safety The reliability and safety principle means AI systems should operate reliably and safely, including through testing and validation under expected and unexpected conditions.
NEW QUESTION # 114
Which type of compute resource should you use to attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning?
Answer: B
Explanation:
To attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning, you should use the "Attached Compute" or "Kubernetes Compute Target". This allows you to leverage your existing AKS cluster as a compute resource for your machine learning tasks within Azure Machine Learning. You can achieve this using the Azure CLI v2, Python SDK v2, or Machine Learning Studio UI.
1. Kubernetes Compute Target:
Azure Machine Learning treats your AKS cluster as a compute target, allowing you to specify it as the location for running your training jobs or deploying models.
2. Attached Compute:
This refers to the ability to connect existing compute resources, like your AKS cluster, to your Azure Machine Learning workspace.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-to-workspace
NEW QUESTION # 115
You have a dataset that contains experimental data for fuel samples.
You need to predict the amount of energy in kilojoules that can be obtained from a sample based on its measured density.
Which type of AI workload should you use?
Answer: D
Explanation:
Regression is a supervised machine learning technique which is used to predict continuous values. The ultimate goal of the regression algorithm is to plot a best-fit line or a curve between the data. The three main metrics that are used for evaluating the trained regression model are variance, bias and error.
Reference:
https://builtin.com/data-science/regression-machine-learning
NEW QUESTION # 116
......
The web-based Microsoft AI-901 practice test software can be used through browsers like Firefox, Safari, and Google Chrome. The customers don't need to download or install any excessive plugins or software in order to use the web-based Microsoft AI-901 Practice Exam format. The web-based AI-901 practice test software format is supported by different operating systems like Mac, iOS, Linux, Windows, and Android.
AI-901 Reliable Dump: https://www.itexamreview.com/AI-901-exam-dumps.html
BTW, DOWNLOAD part of ITexamReview AI-901 dumps from Cloud Storage: https://drive.google.com/open?id=1ZkBOg9FSClEDvY3Mjyc1zV-iV56n59la