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Quiz HP - Authoritative HPE2-N69 Valid Exam Cram

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    HPE2-N69 exam is a credible and reliable assessment of an individual's understanding of AI development. It tests everything an individual needs to know to become proficient in using HPE Cray AI Development Environment. HPE2-N69 exam is designed to ensure that candidates have attained the necessary skills, knowledge, and experience required to succeed in the dynamic world of AI development. Using HPE Cray AI Development Environment certification exam is a valuable asset for individuals to showcase their high level of expertise in AI development, which is ever in-demand across a broad range of industries.

    HPE Cray AI Development Environment is a powerful platform that enables developers to build and deploy AI solutions quickly and efficiently. It provides a comprehensive set of tools and capabilities that are designed to help developers streamline the entire AI development process, from data preparation to model training and deployment. The HPE2-N69 certification exam covers all the essential concepts and techniques required to work with the HPE Cray AI Development Environment effectively.

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    HP Using HPE Cray AI Development Environment Sample Questions (Q30-Q35):

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

    Answer: C

    Explanation:
    The OS supported for setting up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined on a local machine is Red Hat 7-based Linux. Red Hat 7-based Linux is an open source operating system that is used extensively in enterprise applications. It provides a stable and secure platform for running applications and is suitable for use in a demo cluster.


    NEW QUESTION # 31
    A customer is deploying HPE Machine learning Development Environment on on-prem infrastructure. The customer wants to run some experiments on servers with 8 NVIDIA A too GPUs and other experiments on servers with only Z NVIDIA T4 GPUs. What should you recommend?

    • A. Deploying servers with 8 GPUs as agents and using the conductor to run experiments that require only 2 GPUs
    • B. Letting the conductor automatically determine which servers to use for each experiment, based on the number of resource slots required
    • C. Deploying two HPE Machine Learning Development Environment clusters, one tor each server type
    • D. Establishing multiple compute resource pools on the cluster, one tor servers or each type

    Answer: D

    Explanation:
    By establishing multiple compute resource pools on the cluster, you can ensure that the correct servers are used for each experiment, depending on the number of GPUs required. This will help ensure that the experiments are run on the servers with the correct resources without having to manually assign each experiment to the appropriate server.


    NEW QUESTION # 32
    What is one key target vertical (or HPE Machine Learning Development solutions?

    • A. Manufacturing
    • B. Hospitality
    • C. K-12education
    • D. Retail

    Answer: A

    Explanation:
    One key target vertical for HPE Machine Learning Development solutions is Manufacturing. Manufacturing businesses are using machine learning to automate processes, reduce costs, and improve safety and quality control. HPE ML solutions provide the tools and technologies to help manufacturers develop and deploy ML models in their production environments, enabling them to optimize and automate their operations.


    NEW QUESTION # 33
    What distinguishes deep learning (DL) from other forms of machine learning (ML)?

    • A. Models that are trained through unsupervised, rather than supervised, training
    • B. Models based on neural networks with interconnected layers of nodes, including multiple hidden layers
    • C. Models trained through multiple training processes implemented by different team members
    • D. Models defined with Apache Spark rather than MapReduce

    Answer: A


    NEW QUESTION # 34
    You are meeting with a customer, and MUDL engineers express frustration about losing work flue to hardware failures. What should you explain about how HPE Machine Learning Development Environment addresses this pain point?

    • A. The solution automatically mirrors the training process on redundant agents, which take over If an issue occurs.
    • B. The conductor and each of the agents ate deployed in an active-standby model, which protects in case of hardware issues.
    • C. The solution can take periodic checkpoints during the training process and automatically restart failed training from the latest checkpoint.
    • D. The solution continuously monitors agent hardware and sends out proactive alerts before failed hardware causes training to tail.

    Answer: A


    NEW QUESTION # 35
    ......

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