Sep-2023 New Version HPE2-N69 Certificate & Helpful Exam Dumps is Online [Q13-Q32]

NEW QUESTION 13
You are meeting with a customer how has several DL models deployed. Out wants to expand the projects.
The ML/DL team is growing from 5 members to 7 members. To support the growing team, the customer has assigned 2 dedicated IT start. The customer is trying to put together an on-prem GPU cluster with at least 14 CPUs.
What should you determine about this customer?

The customer is not ready for an HPE Machine Learning Development solution, but you could recommend open-source Determined Al.

The customer is not ready for an HPE Machine Learning Development solution. Out you could recommend an educational HPE Pointnext ASPS workshop.

The customer is a key target for HPE Machine Learning Development Environment, but not HPE Machine Learning Development System.

The customer is a key target for an HPE Machine Learning Development solution, and you should continue the discussion.

NEW QUESTION 14
ML engineers are defining a convolutional neural network (CNN) model bur they are not sure how many filters to use in each convolutional layer. What can help them address this concern?

Using hyperparameter optimization (HPO)

Distributing the training across multiple CPUs

Using a variable learning late

Training the model on multiple epochs

NEW QUESTION 15
Where does TensorFlow fit in the ML/DL Lifecycle?

it helps engineers use a language like Python to code and trail DL models.

it provides pipelines to manage the complete lifecycle.

It is primarily used to transport trained models to a deployment environment.

It adds system and GPU monitoring to the training process.

NEW QUESTION 16
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?

installing the NVIDIA Container Toolkit on your local machine

Manually creating the AWS EC2 instance with a PostgreSQL database

Recording the name of a valid AWS EC2 keypair

Adding Amazon Elastic Kubernetes Services (EKS) to your AWS account

NEW QUESTION 17
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?

Validation refers to testing how well the current model performs on new data; file lower the loss the better the performance.

Validation refers to an assessment of how efficient the model code is; the lower the loss the lower the demand on GPU memory resources.

Validation loss refers to the loss detected during the backward pass of training, while training loss refers to loss during the forward pass.

Validation loss is metadata that indicates how many updates were lost between the conductor and agents.

NEW QUESTION 18
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?

Streaming requires just one bucket, while downloading requires many.

The trial can more quickly start up and begin training the model.

The trial can better separate training and validation data.

Setting up streaming is easier that setting up downloading.

NEW QUESTION 19
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?

Under “searcher,” set “max_concurrent_trails” to cap the number of trials run at once by this experiment.

Under “searcher,” set “divisor- to 2 to reduce the share of the resource slots that the experiment receives.

Set the “scheduling_unit” to cap the number of resource slots used at once by this experiment.

Under “resources.- set ‘priority to I to reduce the share of the resource slots mat the experiment receives.

NEW QUESTION 20
What type of interconnect does HPE Machine learning Development System use for high-speed, agent-to-agent communications?

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

Slingshot

InfiniBand

Data Center Bridging (OCB)-enabled Ethernet

NEW QUESTION 21
What is one of the responsibilities of the conductor of an HPE Machine Learning Development Environment cluster?

it downloads datasets for training.

It uploads model checkpoints.

It validates trained models.

It ensures experiment metadata is stored.

NEW QUESTION 22
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?

Time-consuming data collection

Complex model deployment processes

Complex and time-consuming data cleansing process

Complex and time-consuming hyperparameter optimization (HPO)

NEW QUESTION 23
What are the mechanics of now a model trains?

Decides which algorithm can best meet the use case for the application in question

Adjusts the model’s parameter weights such that the model can Better perform its tasks

Tests how accurately the model performs on a wide array of real world data

Detects Data drift of content drift that might compromise the ML model’s performance

NEW QUESTION 24
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?

Validation refers to testing how well the current model performs on new data; file lower the loss the better the performance.

Validation refers to an assessment of how efficient the model code is; the lower the loss the lower the demand on GPU memory resources.

Validation loss refers to the loss detected during the backward pass of training, while training loss refers to loss during the forward pass.

Validation loss is metadata that indicates how many updates were lost between the conductor and agents.

NEW QUESTION 25
You are in a directory on your machine with your experiment config file and your model code. You enter this command:
det experiment create myfile.yaml
You receive this error:
det experiment create: error: the following arguments are required: model_def What should you do?

Re-enter the command with “-m” in which is the code filename.

Make sure that the myfile.yaml tile includes code tor a PyTorchTrial or TFKerasTrial class.

Re-enter the command with a period (.) at the end.

Make sure that you have already logged into the cluster with the “det login” command.

NEW QUESTION 26
A customer is deploying HPE Machine learning Development Environment on on-prem infrastructure. The customer wants to run some experiments on servers with 8 NVIDIA A too GPUs and other experiments on servers with only Z NVIDIA T4 GPUs. What should you recommend?

Letting the conductor automatically determine which servers to use for each experiment, based on the number of resource slots required

Deploying two HPE Machine Learning Development Environment clusters, one tor each server type

Deploying servers with 8 GPUs as agents and using the conductor to run experiments that require only 2 GPUs

Establishing multiple compute resource pools on the cluster, one tor servers or each type

NEW QUESTION 27
What is a benefit of HPE Machine Learning Development Environment, beyond open source Determined AI?

Automated user provisioning

Pipeline-based data management

Distributed training

Automated hyperparameter optimization (HPO)

NEW QUESTION 28
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?

Streaming requires just one bucket, while downloading requires many.

The trial can more quickly start up and begin training the model.

The trial can better separate training and validation data.

Setting up streaming is easier that setting up downloading.

NEW QUESTION 29
A company has recently expanded its ml engineering resources from 5 CPUs 1012 GPUs.
What challenge is likely to continue to stand in the way of accelerating deep learning (DU training?

A lack of understanding of the DL model architecture by the NL engineering team

The complexity of adjusting model code to distribute the training process across multiple GPUs

A lack of adequate power and cooling for the GPU-enabled servers

The requirement that the ML team must wait for the IT team to initiate each new training process

NEW QUESTION 30
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?

HP-UX v11i

Windows Server 2016 or above

Windows 10 or above

Red Hat 7-based Linux

NEW QUESTION 31
Your cluster uses Amazon S3 to store checkpoints. You ran an experiment on an HPE Machine Learning Development Environment cluster, you want to find the location tor the best checkpoint created during the experiment. What can you do?

In the experiment config that you used, look for the “bucket” field under “hyperparameters.” This is the UUID for checkpoints.

Use the “det experiment download -top-n I” command, referencing the experiment ID.

In the Web Ul, go to the Task page and click the checkpoint task that has the experiment ID.

Look for a “determined-checkpoint/” bucket within Amazon S3, referencing your experiment ID.

NEW QUESTION 32
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 for “resources_per_trial?

10

24

12

20