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Exam DP-100 topic 4 question 51 discussion

Actual exam question from Microsoft's DP-100
Question #: 51
Topic #: 4
[All DP-100 Questions]

DRAG DROP
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You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.

The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must preview the data profile in Azure Machine Learning studio once the dataset is created.

You need to train the model.

Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

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Suggested Answer:
by adamcodes716 at April 26, 2023, 11:48 a.m.

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sl_mslconsulting
5 months ago
If you follow along closely with the steps detailed in the link provided by paperflying: Create an Automated Machine Learning job Create and load a dataset as a data asset ( I would pick tabular as this is the default and only option supported by Auto ML. Also you can preview the data at this step) create an experiment ( part of the configure job task) create compute target ( part of the configure job task) Again this is strictly following the steps outlined in the doc and you don't need to agree.
upvoted 1 times
sl_mslconsulting
5 months ago
In the newest UI, you specify the experiment name in the "Basic settings" step, which comes before the "Task type & data". So you just have to decide the orders yourself.
upvoted 1 times
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PI_Team
1 year, 2 months ago
Create a tabular dataset. Create a compute cluster. Create an experiment. Create an automated ML job. First, you need to create a tabular dataset that contains the data you want to use to train the model. You can do this by uploading a file or connecting to an external data source in Azure Machine Learning studio. Once the dataset is created, you can preview the data profile in Azure Machine Learning studio. Next, you need to create a compute cluster that will be used to run the automated ML job. After creating the compute cluster, you need to create an experiment to track the runs of your automated ML job. An experiment is a named container for a series of related runs. Finally, you need to create an automated ML job SaM
upvoted 2 times
PI_Team
9 months, 3 weeks ago
I need to make corrections here. I went through it myself. The first thing you will do on Azure Ml is going to Azure Auto ML job, then it asks you for a name for the experiment (so create the experiment), then you can import data where you can see the data as well, indeed a preview of the dataset. Finally, you will create or choose the compute cluster and then you will submit the experiment. So, I still don't know what this question is asking specifically, but I would go with the order I mentioned in the updated comment. SaM
upvoted 1 times
deyoz
8 months, 1 week ago
you are right but i think as you are creating automated ML job you need to select the dataset, environment, then select compute cluster. That means these objects should have already been created. Therefore, logically, your earlier answer seems to be correct for me.
upvoted 1 times
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phdykd
1 year, 3 months ago
Create a tabular dataset Create a compute cluster Create an experiment Create an automated ML job
upvoted 4 times
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vish9
1 year, 5 months ago
Automated ML only supports Tabular dataset https://learn.microsoft.com/en-us/azure/machine-learning/v1/how-to-create-register-datasets?view=azureml-api-1
upvoted 1 times
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paperflying
1 year, 6 months ago
Upload the file and preview. https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-first-experiment-automated-ml?view=azureml-api-2
upvoted 1 times
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adamcodes716
1 year, 6 months ago
Why not tabular dataset?
upvoted 1 times
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