Microsoft AZ900 Exam Dumps|QAs Page -4

Last updated on July 14th, 2024 at 12:01 am

Microsoft AZ900 Exam Dumps post contains real and latest questions for Microsoft Azure Fundamentals.

Microsoft AZ900 Exam Dumps – QAs 16-20

Q16. This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.
You are planning to make use of Azure Machine Learning designer to train models.
You need choose a suitable compute type.
Recommendation: You choose Inference cluster.
Will the requirements be satisfied?

1. Yes
2. No

Q17. You are making use of the Azure Machine Learning to designer construct an experiment.
After dividing a dataset into training and testing sets, you configure the algorithm to be Two-Class Boosted Decision Tree.
You are preparing to ascertain the Area Under the Curve (AUC).
Which of the following is a sequential combination of the models required to achieve your goal?

1. Train, Score, Evaluate.
2. Score, Evaluate, Train.
3. Evaluate, Export Data, Train.
4. Train, Score, Export Data.

Q18. Your team is building a data engineering and data science development environment.
The environment must support the following requirements:
✑ support Python and Scala
✑ compose data storage, movement, and processing services into automated data pipelines
✑ the same tool should be used for the orchestration of both data engineering and data science
✑ support workload isolation and interactive workloads
✑ enable scaling across a cluster of machines
You need to create the environment.
What should you do?

1. Build the environment in Apache Hive for HDInsight and use Azure Data Factory for orchestration.
2. Build the environment in Azure Databricks and use Azure Data Factory for orchestration.
3. Build the environment in Apache Spark for HDInsight and use Azure Container Instances for orchestration.
4. Build the environment in Azure Databricks and use Azure Container Instances for orchestration.

Q19. You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size.
You have the following requirements:
✑ Models must be built using Caffe2 or Chainer frameworks.
✑ Data scientists must be able to use a data science environment to build the machine learning pipelines and train models on their personal devices in both connected and disconnected network environments.
Personal devices must support updating machine learning pipelines when connected to a network.
You need to select a data science environment.
Which environment should you use?

1. Azure Machine Learning Service
2. Azure Machine Learning Studio
3. Azure Databricks
4. Azure Kubernetes Service (AKS)

Q20. You must store data in Azure Blob Storage to support Azure Machine Learning.
You need to transfer the data into Azure Blob Storage.
What are three possible ways to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

1. Bulk Insert SQL Query
2. AzCopy
3. Python script
4. Azure Storage Explorer
5. Bulk Copy Program (BCP)