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HP HPE2-N69 Exam Syllabus Topics:

Topic	Details
Topic 1	Describe the HPE Machine Learning Development Environment software architecture and deployment options Have a conversation with customers about machine learning (ML) and deep learning (DL)
Topic 2	Explain how HPE Machine Learning Development Environment helps customers surmount their challenges Run a proof of concept (PoC)
Topic 3	Demonstrate running a variety of experiment types on the HPE Machine Learning Development Environment Describe how HPE Machine Learning Development Environment fits in the market

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HP Using HPE Cray AI Development Environment Sample Questions (Q28-Q33):

NEW QUESTION # 28
You want to set up a simple demo cluster for HPE Machine Learning Development Environment (or the open source Determined Al) on Amazon Web Services (AWS). You plan to use "det deploy" to set up the cluster.
What is one prerequisite?

• A. installing the NVIDIA Container Toolkit on your local machine
• B. Manually creating the AWS EC2 instance with a PostgreSQL database
• C. Recording the name of a valid AWS EC2 keypair
• D. Adding Amazon Elastic Kubernetes Services (EKS) to your AWS account

Answer: A
NEW QUESTION # 29
What is a reason to use the best tit policy on an HPE Machine Learning Development Environment resource pool?

• A. Ensuring that all experiments receive their fair share of resources
• B. Equally distributing utilization across multiple agents
• C. Ensuring that the highest priority experiments obtain access to more resources
• D. Minimizing costs in a cloud environment

Answer: C Explanation:
The best fit policy on an HPE Machine Learning Development Environment resource pool ensures that the highest priority experiments obtain access to more resources, while still ensuring that all experiments receive their fair share. This allows you to make the most of your resources and prioritize the experiments that are most important to you.
NEW QUESTION # 30
You want to set up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined all on a local machine. Which OS Is supported?

• A. Windows 10 or above
• B. HP-UX v11i
• C. Windows Server 2016 or above
• D. Red Hat 7-based Linux

Answer: B
NEW QUESTION # 31
A trial is running on a GPU slot within a resource pool on HPE Machine Learning Development Environment. That GPU fails. What happens next?

• A. The trial tails, and the ML engineer must restart it manually by re-running the experiment.
• B. The conductor reschedules the trial on another available GPU in the pool, and the trial restarts from the latest checkpoint.
• C. The concluded reschedules the trial on another available GPU in the pool, and the trial restarts from the state of the latest training workload.
• D. The trial fails, and the ML engineer must manually restart it from the latest checkpoint using the WebUI.

Answer: B Explanation:
If a GPU fails during a trial running on a resource pool on HPE Machine Learning Development Environment, the conductor will reschedule the trial on another available GPU in the pool, and the trial will restart from the latest checkpoint. The trial will not fail, and the ML engineer will not have to manually restart it from the latest checkpoint using the WebUI.
NEW QUESTION # 32
What is a benefit or HPE Machine Learning Development Environment, beyond open source Determined AI?

• A. Model Inferencing
• B. Experiment tracking
• C. Distributed training
• D. Premium dedicated support

Answer: B
NEW QUESTION # 33
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