Home

Home / HP / HPE2-N69

Question list

List of questions

Question 1

(0)

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

Question 2

(0)

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

Question 3

(0)

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

Question 4

(0)

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 d

Question 5

(0)

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 "validat

Question 6

(0)

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?

Question 7

(0)

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

Question 8

(0)

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?

Question 9

(0)

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?

Question 10

(0)

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 taki

Open VPLUS File

Convert VPLUS to PDF

Related questions

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?

What role do HPE ProLiant DL325 servers play in HPE Machine Learning Development System?

You are proposing an HPE Machine Learning Development Environment solution for a customer. On what do you base the license count?

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?

What is a benefit of HPE Machine Learning Development Environment mat tends to resonate with executives?

At what FQDN (or IP address) do users access the WebUI Tor an HPE Machine Learning Development cluster?

Compared to Asynchronous Successive Halving Algorithm (ASHA), what is an advantage of Adaptive ASHA?

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?

An HPE Machine Learning Development Environment resource pool uses priority scheduling with preemption disabled. Currently Experiment 1 Trial I is using 32 of the pool's 40 total slots; it has priority 42. Users then run two more experiments: • Experiment 2:1 trial (Trial 2) that needs 24 slots; priority 50 • Experiment 3; l trial (Trial 3) that needs 24 slots; priority I What happens?

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

Question 31 - HPE2-N69 discussion

Report

Where does TensorFlow fit in the ML/DL Lifecycle?

A.

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

B.

it provides pipelines to manage the complete lifecycle.

C.

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

D.

It adds system and GPU monitoring to the training process.

Show Answer

asked 16/09/2024

Rutger Pels

32 questions

User

Your answer: A B C D

0 comments

Sorted by

Leave a comment first