Download HP Using HPE AI and Machine Learning.HPE2-N69.VCEplus.2024-08-23.31q.tqb

Vendor: HP
Exam Code: HPE2-N69
Exam Name: HP Using HPE AI and Machine Learning
Date: Aug 23, 2024
File Size: 306 KB

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Demo Questions

Question 1
What common challenge do ML teams lace in implementing hyperparameter optimization (HPO)?
  1. HPO is a joint ml and IT Ops effort, and engineers lack deep enough integration with the IT team.
  2. They cannot implement HPO on TensorFlow models, so they must move their models to a new framework.
  3. Implementing HPO manually can be time-consuming and demand a great deal of expertise.
  4. ML teams struggle to find large enough data sets to make HPO feasible and worthwhile.
Correct answer: A
Question 2
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 tor "resources_per_trial?
  1. 10
  2. 24
  3. 12
  4. 20
Correct answer: A
Question 3
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?
  1. The solution automatically mirrors the training process on redundant agents, which take over If an issue occurs.
  2. The solution continuously monitors agent hardware and sends out proactive alerts before failed hardware causes training to tail.
  3. The conductor and each of the agents ate deployed in an active-standby model, which protects in case of hardware issues.
  4. The solution can take periodic checkpoints during the training process and automatically restart failed training from the latest checkpoint.
Correct answer: A
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