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NEW QUESTION 36
An ML engineer is running experiments on HPE Machine Learning Development Environment. The engineer notices all of the checkpoints for a trial except one disappear after the trial ends. The engineer wants to Keep more of these checkpoints. What can you recommend?

A. Adjusting the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage.B. Adjusting how many of the latest and best checkpoints are saved in the experiment config's checkpoint storage settings.C. Monitoring ongoing trials In the WebUl and clicking checkpoint nags to auto-save the desired checkpoints.D. Double-checking that the checkpoint storage location is operating under 90% of total capacity.

Answer: A

 

NEW QUESTION 37
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?

A. Validation refers to testing how well the current model performs on new data; file lower the loss the better the performance.B. Validation loss is metadata that indicates how many updates were lost between the conductor and agents.C. Validation refers to an assessment of how efficient the model code is; the lower the loss the lower the demand on GPU memory resources.D. Validation loss refers to the loss detected during the backward pass of training, while training loss refers to loss during the forward pass.

Answer: D

 

NEW QUESTION 38
What is one key target vertical (or HPE Machine Learning Development solutions?

A. ManufacturingB. K-12educationC. RetailD. Hospitality

Answer: A

 

NEW QUESTION 39
You want to open the conversation about HPE Machine Learning Development Environment with an IT contact at a customer. What can be a good discovery question?

A. How long does it currently take for a DL training to run the backward pass?B. How much time do you spend managing the ML infrastructure?C. How much do you understand about building ML and DL models?D. What frustrations do you have with existing ML deployment and differencing solutions?

Answer: A

 

NEW QUESTION 40
What is a reason to use the best tit policy on an HPE Machine Learning Development Environment resource pool?

A. Ensuring that the highest priority experiments obtain access to more resourcesB. Minimizing costs in a cloud environmentC. Equally distributing utilization across multiple agentsD. Ensuring that all experiments receive their fair share of resources

Answer: B

 

NEW QUESTION 41
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