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

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Vendor: HP
Exam Code: HPE2-N69
Exam Name: HP Using HPE AI and Machine Learning
Date: Aug 23, 2024
File Size: 226 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
Question 4
At what FQDN (or IP address) do users access the WebUI Tor an HPE Machine Learning Development cluster?
  1. Any of the agent's in a compute pool
  2. A virtual one assigned to the cluster
  3. The conductor's
  4. Any of the agent's in an aux pool
Correct answer: D
Question 5
What is the role of a hidden layer in an artificial neural network (ANN)?
  1. It is responsible for passively reformatting data for use in the ANN.
  2. It is responsible for making the final decision about how to label a record, based on weighted input from preceding layers.
  3. It receives and weighs inputs from the preceding layer and produces outputs for the next layer.
  4. It does not play a role during the forward pass of data through the ANN, but it helps to optimize during the backward pass.
Correct answer: D
Question 6
A company has an HPE Machine Learning Development Environment cluster. The ML engineers store training and validation data sets in Google Cloud Storage (GCS). What is an advantage of streaming the data during a trial, as opposed to downloading the data?
  1. Streaming requires just one bucket, while downloading requires many.
  2. The trial can more quickly start up and begin training the model.
  3. The trial can better separate training and validation data.
  4. Setting up streaming is easier that setting up downloading.
Correct answer: C
Question 7
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?
  1. Validation refers to testing how well the current model performs on new data; file lower the loss the better the performance.
  2. Validation refers to an assessment of how efficient the model code is; the lower the loss the lower the demand on GPU memory resources.
  3. Validation loss refers to the loss detected during the backward pass of training, while training loss refers to loss during the forward pass.
  4. Validation loss is metadata that indicates how many updates were lost between the conductor and agents.
Correct answer: C
Question 8
An ml engineer wants to train a model on HPE Machine Learning Development Environment without implementing hyper parameter optimization (HPO). What experiment config fields configure this behavior?
  1. profiling: enabled: false
  2. hyperparameters; optimizer:none
  3. searcher: name: single
  4. resources: slots_per_trial: 1
Correct answer: D
Question 9
What is a benefit of HPE Machine Learning Development Environment, beyond open source Determined AI?
  1. Automated user provisioning
  2. Pipeline-based data management
  3. Distributed training
  4. Automated hyperparameter optimization (HPO)
Correct answer: B
Question 10
A customer has Men expanding its deep learning (DO prefects and is confronting several challenges.
Which of these challenges does HPE Machine Learning Development Environment specifically address?
  1. Time-consuming data collection
  2. Complex model deployment processes
  3. Complex and time-consuming data cleansing process
  4. Complex and time-consuming hyperparameter optimization (HPO)
Correct answer: C
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