Most UptoDate HP HPE2-N69 Exam Dumps PDF 2023 [Q25-Q40]

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Most UptoDate HP HPE2-N69 Exam Dumps PDF 2023

100% Free HPE Product Certified – AI and Machine Learning HPE2-N69 Dumps PDF Demo Cert Guide Cover

To be eligible for taking the HP HPE2-N69 exam, candidates must have a basic understanding of AI concepts and programming languages such as Python. They should also have experience in using HPE Cray AI Development Environment for developing and deploying AI applications. HPE2-N69 exam consists of 50 multiple-choice questions, and candidates have 90 minutes to complete it. The passing score for HPE2-N69 exam is 70%.

HP HPE2-N69 exam is designed to test the candidate’s knowledge and skills in using the HPE Cray AI Development Environment. HPE2-N69 exam is primarily intended for IT professionals who want to acquire expertise in using the HPE Cray AI Development Environment to develop, deploy, and maintain artificial intelligence (AI) solutions. HPE2-N69 exam covers a range of topics, including data preparation, model training, model deployment, and model monitoring, among others.

NEW QUESTION 25
An ml engineer wants to train a model on HPE Machine Learning Development Environment without implementing hyper parameter optimization (HPO). What experiment config fields configure this behavior?

profiling: enabled: false

hyperparameters; optimizer:none

searcher: name: single

resources: slots_per_trial: 1

NEW QUESTION 26
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 27
What common challenge do ML teams lace in implementing hyperparameter optimization (HPO)?

HPO is a joint ml and IT Ops effort, and engineers lack deep enough integration with the IT team.

They cannot implement HPO on TensorFlow models, so they must move their models to a new framework.

Implementing HPO manually can be time-consuming and demand a great deal of expertise.

ML teams struggle to find large enough data sets to make HPO feasible and worthwhile.

NEW QUESTION 28
You are meeting with a customer, and MUDL engineers express frustration about losing work flue to hardware failures. What should you explain about how HPE Machine Learning Development Environment addresses this pain point?

The solution automatically mirrors the training process on redundant agents, which take over If an issue occurs.

The solution continuously monitors agent hardware and sends out proactive alerts before failed hardware causes training to tail.

The conductor and each of the agents ate deployed in an active-standby model, which protects in case of hardware issues.

The solution can take periodic checkpoints during the training process and automatically restart failed training from the latest checkpoint.

NEW QUESTION 29
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 30
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 31
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 better separate training and validation data.

Setting up streaming is easier that setting up downloading.

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

NEW QUESTION 32
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 33
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 34
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 35
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 36
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?

Kubernetes

PyTorch

Terralorm

Docker

NEW QUESTION 37
You are helping a customer start to implement hyper parameter optimization (HPO) with HPE Machine learning Development Environment. An ML engineer is putting together an experiment config file with the desired Adaptive A5HA settings. The engineer asks you questions, such as how many trials will be trained on the max length and what the min length for all trials will be.
What should you explain?

The engineer should run the “det preview-search” command, referencing the experiment config.

The engineer should access the HPE Machine Learning Development online calculator and input the mode, max_trials, max_length, divisor, and max_runs.

The engineer should upload the experiment config to the HPE Machine Learning Development Environment WebUl and view the graph of the experiment plan.

The engineer should run a preliminary experiment with one tenth the desired number of max trials, assess the results, and then run the full experiment.

NEW QUESTION 38
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?

Adjusting how many of the latest and best checkpoints are saved in the experiment config’s checkpoint storage settings.

Monitoring ongoing trials In the WebUl and clicking checkpoint nags to auto-save the desired checkpoints.

Double-checking that the checkpoint storage location is operating under 90% of total capacity.

Adjusting the checkpoint storage settings to save checkpoints to a shared file system instead of cloud storage.

NEW QUESTION 39
What is the role of a hidden layer in an artificial neural network (ANN)?

It is responsible for passively reformatting data for use in the ANN.

It is responsible for making the final decision about how to label a record, based on weighted input from preceding layers.

It receives and weighs inputs from the preceding layer and produces outputs for the next layer.

It does not play a role during the forward pass of data through the ANN, but it helps to optimize during the backward pass.

NEW QUESTION 40
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.