Cyber Monday 2024! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Microsoft Exam AI-900 Topic 5 Question 61 Discussion

Actual exam question for Microsoft's AI-900 exam
Question #: 61
Topic #: 5
[All AI-900 Questions]

You plan to use Azure Machine Learning Studio and automated machine learning (automated ML) to build and train a model What should you create first?

Show Suggested Answer Hide Answer
Suggested Answer: B

by Solange at Apr 12, 2024, 09:35 PM

Limited Time Offer

25%

Off

Get Premium AI-900 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel
Crista
5 months ago
Having a registered dataset ensures data integrity and reusability.
upvoted 0 times
...
Reta
5 months ago
Why is that?
upvoted 0 times
...
Crista
5 months ago
I would actually create a registered dataset first.
upvoted 0 times
...
Tegan
6 months ago
It provides a centralized place to experiment and train models.
upvoted 0 times
...
Matthew
6 months ago
Why do you think that?
upvoted 0 times
...
Tegan
6 months ago
I think we should create a Machine Learning workspace first.
upvoted 0 times
...
Providencia
6 months ago
But without the workspace, where will you store and manage the project?
upvoted 0 times
...
Jerrod
6 months ago
That makes sense, having the dataset ready is crucial for training the model
upvoted 0 times
...
Graciela
7 months ago
Actually, I believe we should create a registered dataset first to have the data ready
upvoted 0 times
...
Providencia
7 months ago
I agree with creating the workspace is the foundation for the project
upvoted 0 times
...
Jerrod
7 months ago
I think we should create a Machine Learning workspace first
upvoted 0 times
...
Annabelle
8 months ago
You guys are right, the workspace is definitely the first thing you should create. Although, I have to admit, a Jupyter notebook could also be helpful for playing around with the automated ML features. But the workspace is still the essential starting point.
upvoted 0 times
...
Freeman
8 months ago
Hmm, I'm leaning towards C) a registered dataset. That's the data we're going to be working with, so it makes sense to get that sorted out first.
upvoted 0 times
...
Goldie
8 months ago
Yeah, I was thinking the same thing. Creating the workspace first just makes the most logical sense. Once you have that set up, then you can start working on the other pieces like the dataset and the designer pipeline.
upvoted 0 times
...
Cecil
8 months ago
You guys are all wrong. The correct answer is clearly B) a Machine Learning workspace. That's the hub where rything else happens.
upvoted 0 times
...
Claudio
8 months ago
I agree with Adell. The Machine Learning workspace is the foundation you need to build everything else on. Without that, you won't be able to access the automated ML tools or any of the other Azure ML services.
upvoted 0 times
Zita
6 months ago
I agree. It's the starting point for using Azure Machine Learning Studio.
upvoted 0 times
...
Cory
7 months ago
B) a Machine Learning workspace
upvoted 0 times
...
...
Emeline
8 months ago
Hold on, what about the Jupyter notebook? Isn't that where we do a lot of the exploratory data analysis and model experimentation?
upvoted 0 times
...
Adell
8 months ago
Hmm, this seems like a straightforward question. I think the answer is B) a Machine Learning workspace. That's the core component you need to set up before you can start using Azure Machine Learning Studio and automated ML.
upvoted 0 times
...
Hershel
8 months ago
Nah, I disagree. I think the Machine Learning designer pipeline is the way to go. That's where you actually build and train the model, isn't it?
upvoted 0 times
...
Leonida
8 months ago
I'm not so sure. I think you might need to have a registered dataset first, before you can do anything else. That's the foundation, isn't it?
upvoted 0 times
Jackie
7 months ago
That sounds right. Then you can move on to building a model with Azure Machine Learning Studio.
upvoted 0 times
...
Carmelina
7 months ago
So, the correct order would be: create a Machine Learning workspace, then a registered dataset?
upvoted 0 times
...
Renato
7 months ago
Yes, that's important too. It provides the environment for your work.
upvoted 0 times
...
Elizabeth
7 months ago
But don't we also need a Machine Learning workspace to work in Azure Machine Learning Studio?
upvoted 0 times
...
Amalia
7 months ago
I agree, that's the foundation for building and training a model.
upvoted 0 times
...
Adolph
8 months ago
I think you should create a registered dataset first.
upvoted 0 times
...
...
Dewitt
8 months ago
Hmm, this is a tricky one. I suppose the first step would be to create a Machine Learning workspace, right? That seems like the logical starting point to me.
upvoted 0 times
...

Save Cancel