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HP Using HPE Cray AI Development Environment Sample Questions (Q13-Q18):

NEW QUESTION # 13
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 much do you understand about building ML and DL models?
• B. How long does it currently take for a DL training to run the backward pass?
• C. What frustrations do you have with existing ML deployment and differencing solutions?
• D. How much time do you spend managing the ML infrastructure?

Answer: C Explanation:
A good discovery question to start a conversation about HPE Machine Learning Development Environment with an IT contact at a customer would be: "What frustrations do you have with existing ML deployment and differencing solutions?" By understanding the customer's current challenges and frustrations, you can better determine how HPE's ML Development Environment could help to address those needs.
NEW QUESTION # 14
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. Double-checking that the checkpoint storage location is operating under 90% of total capacity.
• B. Adjusting the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage.
• C. Adjusting how many of the latest and best checkpoints are saved in the experiment config's checkpoint storage settings.
• D. Monitoring ongoing trials In the WebUl and clicking checkpoint nags to auto-save the desired checkpoints.

Answer: C Explanation:
The best recommendation for an ML engineer running experiments on HPE Machine Learning Development Environment to keep more of the checkpoints is to adjust the experiment config's checkpoint storage settings to save more of the latest and best checkpoints. This can be done by monitoring ongoing trials in the WebUI and clicking checkpoint flags to auto-save the desired checkpoints. Additionally, the engineer should double-check that the checkpoint storage location is operating under 90% of total capacity to ensure that enough capacity is available to store the checkpoints. Finally, they can adjust the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage if desired.
NEW QUESTION # 15
What is the role of a hidden layer in an artificial neural network (ANN)?

• A. It is responsible for passively reformatting data for use in the ANN.
• B. It is responsible for making the final decision about how to label a record, based on weighted input from preceding layers.
• C. It does not play a role during the forward pass of data through the ANN, but it helps to optimize during the backward pass.
• D. It receives and weighs inputs from the preceding layer and produces outputs for the next layer.

Answer: C
NEW QUESTION # 16
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?

• A. Complex model deployment processes
• B. Time-consuming data collection
• C. Complex and time-consuming hyperparameter optimization (HPO)
• D. Complex and time-consuming data cleansing process

Answer: C Explanation:
The HPE Machine Learning Development Environment specifically addresses Complex and time-consuming hyperparameter optimization (HPO). HPO is a process used to identify the most effective set of hyperparameters for a given machine learning model. HPE's ML Development Environment provides a suite of tools that allow users to quickly and easily design and deploy deep learning models, as well as optimize their hyperparameters to get the best results.
NEW QUESTION # 17
You want to set up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined all on a local machine. Which OS Is supported?

• A. Red Hat 7-based Linux
• B. Windows 10 or above
• C. HP-UX v11i
• D. Windows Server 2016 or above

Answer: A Explanation:
The OS supported for setting up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined on a local machine is Red Hat 7-based Linux. Red Hat 7-based Linux is an open source operating system that is used extensively in enterprise applications. It provides a stable and secure platform for running applications and is suitable for use in a demo cluster.
NEW QUESTION # 18
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