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NEW QUESTION 27
What common challenge do ML teams lace in implementing hyperparameter optimization (HPO)?

• A. They cannot implement HPO on TensorFlow models, so they must move their models to a new framework.
• B. Implementing HPO manually can be time-consuming and demand a great deal of expertise.
• C. ML teams struggle to find large enough data sets to make HPO feasible and worthwhile.
• D. HPO is a joint ml and IT Ops effort, and engineers lack deep enough integration with the IT team.

Answer: B

Explanation:
Implementing hyperparameter optimization (HPO) manually can be time-consuming and demand a great deal of expertise. HPO is not a joint ML and IT Ops effort and it can be implemented on TensorFlow models, so these are not the primary challenges faced by ML teams. Additionally, ML teams often have access to large enough data sets to make HPO feasible and worthwhile.

NEW QUESTION 28
The ML engineer wants to run an Adaptive ASHA experiment with hundreds of trials. The engineer knows that several other experiments will be running on the same resource pool, and wants to avoid taking up too large a share of resources. What can the engineer do in the experiment config file to help support this goal?

• A. Set the "scheduling_unit" to cap the number of resource slots used at once by this experiment.
• B. Under "resources.- set 'priority to I to reduce the share of the resource slots mat the experiment receives.
• C. Under "searcher," set "max_concurrent_trails" to cap the number of trials run at once by this experiment.
• D. Under "searcher," set "divisor- to 2 to reduce the share of the resource slots that the experiment receives.

Answer: C

NEW QUESTION 29
An HPE Machine Learning Development Environment cluster has this resource pool:
Name: pool 1
Location: On-prem
Agents: 2
Aux containers per agent: 100
Total slots: 0
Which type of workload can run In pool I?

• A. Validation
• B. Training
• C. CPU-only Jupyter Notebook
• D. GPU Jupyter Notebook

Answer: C

Explanation:
Pool 1 has two agents, each with 100 aux containers, and a total of 0 slots. This means that the cluster is configured to run CPU-only workloads, such as running a CPU-only Jupyter Notebook. Training, GPU Jupyter Notebook, and validation workloads cannot be run on this cluster due to the lack of GPU resources.

NEW QUESTION 30
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. Complex and time-consuming data cleansing process
• C. Time-consuming data collection
• D. Complex and time-consuming hyperparameter optimization (HPO)

Answer: B

NEW QUESTION 31
You want to set up a simple demo cluster for HPE Machine Learning Development Environment (or the open source Determined Al) on Amazon Web Services (AWS). You plan to use "det deploy" to set up the cluster.
What is one prerequisite?

• A. installing the NVIDIA Container Toolkit on your local machine
• B. Recording the name of a valid AWS EC2 keypair
• C. Adding Amazon Elastic Kubernetes Services (EKS) to your AWS account
• D. Manually creating the AWS EC2 instance with a PostgreSQL database

Answer: A

NEW QUESTION 32
......

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