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HP HPE2-N69 Exam With Confidence Using Practice Dumps

Exam Code:
HPE2-N69
Exam Name:
Using HPE AI and Machine Learning
Certification:
HPE Product Certified - AI and Machine Learning [2022]
Vendor:
HP
Questions:
40
Last Updated:
Dec 22, 2024
Exam Status:
Stable
HP HPE2-N69

HPE2-N69: HPE Product Certified - AI and Machine Learning [2022] Exam 2024 Study Guide Pdf and Test Engine

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Using HPE AI and Machine Learning Questions and Answers

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Question 1

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

Options:

A.

It uses a centralized training architecture that is highly efficient.

B.

It helps DL projects complete faster for a faster ROI.

C.

It helps companies deploy models and generate revenue.

D.

It automatically cleans up data to create better end results.

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Question 2

An HPE Machine Learning Development Environment resource pool uses priority scheduling with preemption disabled. Currently Experiment 1 Trial I is using 32 of the pool's 40 total slots; it has priority 42. Users then run two more experiments:

• Experiment 2:1 trial (Trial 2) that needs 24 slots; priority 50

• Experiment 3; l trial (Trial 3) that needs 24 slots; priority I

What happens?

Options:

A.

Trial I is allowed to finish. Then Trial 3 is scheduled.

B.

Trial 2 is scheduled on 8 of the slots. Then, alter Trial 1 has finished, it receives 16 more slots.

C.

Trial 1 is allowed to finish. Then Trial 2 is scheduled.

D.

Trial 3 is scheduled on 8 of the slots. Then, after Trial 1 has finished, it receives 16 more slots.

Question 3

Refer to the exhibit.

You are demonstrating HPE Machine Learning Development Environment, and you show details about an experiment, as shown in the exhibits. The customer asks about what "validation loss' means. What should you respond?

Options:

A.

Validation refers to testing how well the current model performs on new data; file lower the loss the better the performance.

B.

Validation refers to an assessment of how efficient the model code is; the lower the loss the lower the demand on GPU memory resources.

C.

Validation loss refers to the loss detected during the backward pass of training, while training loss refers to loss during the forward pass.

D.

Validation loss is metadata that indicates how many updates were lost between the conductor and agents.

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