Question No 1

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?

Choose the Choices:

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.

Question No 2

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?

Choose the Choices:

Set the weight to a higher than default value.

Set the weight to a lower than default value.

Set the priority to a lower than default value.

Set the priority to a higher than default value.

Question No 3

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?

Choose the Choices:

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

Question No 4

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?

Choose the Choices:

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.

Question No 5

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?

Choose the Choices:

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.

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