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NEW QUESTION 51
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 run a preliminary experiment with one tenth the desired number of max trials, assess the results, and then run the full experiment.
• B. The engineer should run the "det preview-search" command, referencing the experiment config.
• C. The engineer should access the HPE Machine Learning Development online calculator and input the mode, max_trials, max_length, divisor, and max_runs.
• D. The engineer should upload the experiment config to the HPE Machine Learning Development Environment WebUl and view the graph of the experiment plan.

Answer: A

NEW QUESTION 52
A company has recently expanded its ml engineering resources from 5 CPUs 1012 GPUs.
What challenge is likely to continue to stand in the way of accelerating deep learning (DU training?

• A. A lack of understanding of the DL model architecture by the NL engineering team
• B. The requirement that the ML team must wait for the IT team to initiate each new training process
• C. A lack of adequate power and cooling for the GPU-enabled servers
• D. The complexity of adjusting model code to distribute the training process across multiple GPUs

Answer: A

NEW QUESTION 53
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. Equally distributing utilization across multiple agents
• C. Ensuring that all experiments receive their fair share of resources
• D. Ensuring that the highest priority experiments obtain access to more resources

Answer: A

NEW QUESTION 54
What is a benefit of HPE Machine Learning Development Environment mat tends to resonate with executives?

• A. It automatically cleans up data to create better end results.
• B. It uses a centralized training architecture that is highly efficient.
• C. It helps companies deploy models and generate revenue.
• D. It helps DL projects complete faster for a faster ROI.

Answer: D

NEW QUESTION 55
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 conductor and each of the agents ate deployed in an active-standby model, which protects in case of hardware issues.
• B. The solution automatically mirrors the training process on redundant agents, which take over If an issue occurs.
• C. The solution continuously monitors agent hardware and sends out proactive alerts before failed hardware causes training to tail.
• D. The solution can take periodic checkpoints during the training process and automatically restart failed training from the latest checkpoint.

Answer: B

NEW QUESTION 56
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