HP HPE2-N69 Exam Practice Test Instant Access

Question 1

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?

ATime-consuming data collection

BComplex model deployment processes

CComplex and time-consuming data cleansing process

DComplex and time-consuming hyperparameter optimization (HPO)

Answer : D

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.

Question 2

A trial is running on a GPU slot within a resource pool on HPE Machine Learning Development Environment. That GPU fails. What happens next?

AThe trial tails, and the ML engineer must restart it manually by re-running the experiment.

BThe concluded reschedules the trial on another available GPU in the pool, and the trial restarts from the state of the latest training workload.

CThe conductor reschedules the trial on another available GPU in the pool, and the trial restarts from the latest checkpoint.

DThe trial fails, and the ML engineer must manually restart it from the latest checkpoint using the WebUI.

Answer : C

If a GPU fails during a trial running on a resource pool on HPE Machine Learning Development Environment, the conductor will reschedule the trial on another available GPU in the pool, and the trial will restart from the latest checkpoint. The trial will not fail, and the ML engineer will not have to manually restart it from the latest checkpoint using the WebUI.

Question 3

What type of interconnect does HPE Machine learning Development System use for high-speed, agent-to-agent communications?

ARemote Direct Memory Access (RDMA) overconverged Ethernet (RoCE)

BSlingshot

CInfiniBand

DData Center Bridging (OCB)-enabled Ethernet

Answer : A

HPE Machine Learning Development System uses Remote Direct Memory Access (RDMA) overconverged Ethernet (RoCE) for high-speed, agent-to-agent communications. This technology allows data to be transferred directly between agents without the need for copying, which results in improved performance and reduced latency.

Question 4

A customer is using fair-share scheduling for an HPE Machine Learning Development Environment resource pool. What is one way that users can obtain relatively more resource slots for their important experiments?

ASet the weight to a higher than default value.

BSet the weight to a lower than default value.

CSet the priority to a lower than default value.

DSet the priority to a higher than default value.

Answer : A

Fair-share scheduling allocates resources to experiments based on the weight value of the resource pool. Increasing the weight value of a resource pool will result in more resource slots being allocated to it.

Question 5

A customer mentions that the ML team wants to avoid overfitting models. What does this mean?

AThe team wants to avoid wasting resources on training models with poorly selected hyperparameters.

BThe team wants to spend less time on creating the code tor models and more time training models.

CThe team wants to avoid training models to the point where they perform less well on new data.

DThe team wants to spend less time figuring out which CPUs are available for training models.

Answer : C

Overfitting occurs when a model is trained too closely on the training data, leading to a model that performs very well on the training data but poorly on new data. This is because the model has been trained too closely to the training data, and so cannot generalize the patterns it has learned to new data. To avoid overfitting, the ML team needs to ensure that their models are not overly trained on the training data and that they have enough generalization capacity to be able to perform well on new data.

Question 6

You want to set up a simple demo Ouster tor HPE Machine learning Development Environment for the open source Determined AI) on a local machine. You plan to use "del deploy" to set up the cluster. What software must be installed on the machine before you run that command?

AKubernetes

BPyTorch

CTerralorm

DDocker

Answer : D

Before running the 'del deploy' command to set up the cluster, you must first install Docker on the machine. Docker is a containerization platform that is used to run applications in an isolated environment. It is necessary to have Docker installed before running the 'del deploy' command to set up the cluster for the open source Determined AI on a local machine.

Question 7

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?

AHP-UX v11i

BWindows Server 2016 or above

CWindows 10 or above

DRed Hat 7-based Linux

Answer : D

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.

HP Using HPE AI and Machine Learning HPE2-N69 Exam Practice Test