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Valid HPE2-N69 Exam Duration | VCE HPE2-N69 Dumps

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    HP Using HPE Cray AI Development Environment Sample Questions (Q36-Q41):

    NEW QUESTION # 36
    You are helping a customer start to implement hyper parameter optimization (HPO) with HPE Machine learning Development Environment. An ML engineer is putting together an experiment config file with the desired Adaptive A5HA settings. The engineer asks you questions, such as how many trials will be trained on the max length and what the min length for all trials will be.
    What should you explain?

    • A. The engineer should upload the experiment config to the HPE Machine Learning Development Environment WebUl and view the graph of the experiment plan.
    • B. The engineer should access the HPE Machine Learning Development online calculator and input the mode, max_trials, max_length, divisor, and max_runs.
    • C. The engineer should run a preliminary experiment with one tenth the desired number of max trials, assess the results, and then run the full experiment.
    • D. The engineer should run the "det preview-search" command, referencing the experiment config.

    Answer: B

    Explanation:
    The engineer should specify the number of trials to train on the max length and the minimum length for all trials in the experiment config file. For example, if the engineer wants to run 10 trials with a max length of 10, the config file should look something like this:
    {
    "mode": "A5HA",
    "max_trials": 10,
    "max_length": 10,
    "min_length": 1,
    "divisor": 2,
    "max_runs": 1
    }
    Once the config file is complete, the engineer should upload it to the HPE Machine Learning Development Environment WebUI and view the graph of the experiment plan. This will allow the engineer to see how the Adaptive A5HA settings will affect the experiment. After that, the engineer can run the experiment and assess the results.


    NEW QUESTION # 37
    You are meeting with a customer how has several DL models deployed. Out wants to expand the projects.
    The ML/DL team is growing from 5 members to 7 members. To support the growing team, the customer has assigned 2 dedicated IT start. The customer is trying to put together an on-prem GPU cluster with at least 14 CPUs.
    What should you determine about this customer?

    • A. The customer is a key target for HPE Machine Learning Development Environment, but not HPE Machine Learning Development System.
    • B. The customer is a key target for an HPE Machine Learning Development solution, and you should continue the discussion.
    • C. The customer is not ready for an HPE Machine Learning Development solution, but you could recommend open-source Determined Al.
    • D. The customer is not ready for an HPE Machine Learning Development solution. Out you could recommend an educational HPE Pointnext ASPS workshop.

    Answer: B

    Explanation:
    The customer is a key target for an HPE Machine Learning Development solution, and you should continue the discussion. With the customer's dedicated IT staff, the customer is ready to deploy an on-premise GPU cluster with at least 14 CPUs. The HPE Machine Learning Development Environment is a comprehensive solution that provides the tools and technologies required to develop, manage, and deploy ML models. It includes a distributed training framework, an orchestration layer, a powerful development environment, and an integrated MLOps platform. With this solution, the customer can expand their ML/DL projects and scale up their team.


    NEW QUESTION # 38
    What is a reason to use the best tit policy on an HPE Machine Learning Development Environment resource pool?

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

    Answer: A


    NEW QUESTION # 39
    The 10 agents in "my-compute-poor nave 8 GPUs each, you want to change an experiment config to run on multiple GPUs at once. What Is a valid setting for "resources_per_trial?

    • A. 0
    • B. 1
    • C. 2
    • D. 3

    Answer: D

    Explanation:
    The valid setting for "resourcespertrial" for the 10 agents in "my-compute-poor" with 8 GPUs each would be 20, as this would be the total number of GPUs available across all 10 agents. This setting would allow the experiment config to run on multiple GPUs at once.


    NEW QUESTION # 40
    What is one of the responsibilities of the conductor of an HPE Machine Learning Development Environment cluster?

    • A. It validates trained models.
    • B. It ensures experiment metadata is stored.
    • C. It uploads model checkpoints.
    • D. it downloads datasets for training.

    Answer: C


    NEW QUESTION # 41
    ......

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