Microsoft Certified Power Platform Functional Consultant Associate · Free Practice Question Easy
Question 9
An AI Builder model goes through several stages as it evolves from when you create it through publishing, sharing, and use. After you have finished building your AI model, you're ready to train it.
What is the purpose of training your model?
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A
It learns from your data
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B
It creates the model
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C
It makes it available for use
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D
It makes it stronger
Reveal correct answer
Correct answer: A
Explanation
Your model learns from the data you give it.
An AI Builder model goes through several stages as it evolves from when you create it through publishing, sharing, and use. The following sections describe each of those stages.
Create your model
You can find all the AI Builder model types and capabilities on the Build page, which you can access from the left menu. This page is where you start to create a new custom AI model or select a prebuilt model that you can use right away.
Draft models
When you've made progress building and customizing your AI model, you can save a draft to finish later. You can come back at any time and continue where you left off.
Trained models
After you have finished building your AI model, you're ready to train it. During training, your model learns from your data to perform to your specifications. The time it takes for your model to train depends on the size of your data.
After training is complete, you can view additional training and performance information on the details page. In some cases, you can also quickly test to see your model live in action.
Published models
If you are satisfied with your model, you're ready to publish it. You have to publish a model before it can be available to use in Power Apps and Power Automate, so it's important not to miss this step.
Keep track of your model
Any models you create can be accessed at any time by visiting the Models page, which you can access from the left-side menu in AI Builder. The Models page shows a complete list of your models, as well as their date of the latest training and the various states we've learned about here.
Getting the best model performance for your business can be a rather iterative process. Results can vary depending on the customizations you make to the model, and the training data you provide.
To help facilitate this process, AI Builder allows you to have multiple versions of your model so you can use your model and continue to improve it at the same time.
Edit your model
Editing your model creates a new version that is based on your existing customizations. To edit your model, follow these steps:
Select AI Builder > Models on the left menu.
Find your model and select it to go to its details page.
In the upper-left corner of the screen, select Edit model.
While you edit your model, you can save your work at any time and return it later. The new version will be saved as a draft, which you can access again from your model's details page and by selecting Resume draft.
Work with multiple versions
You can have three versions of your model at any given time:
One published version
One last trained non-published version
One draft version
On the model details page, you can switch between the trained versions using the pivots at the top of the page.
When you edit your model, if you have a published version and a last trained version, you can start from the configuration of either version.
By default, only you can see the models you create and publish. This feature allows you to test them and use them within apps and flows without exposing them.
If you want others to use your model, you can share it with specific users, groups, or your whole organization.
Share your model
Click AI Builder → Models on the left menu.
Find your model name and select it to access its details page.
In the top left corner of the screen, select Share.
Use a shared model
In addition to the models you create yourself, the models that are shared with you by others appear on the Models page, accessible from the left menu.
When a model is shared with you, you have user permissions to use it in apps and flows. You cannot view details or edit the model.
A. Training the AI model is essential as it allows the model to learn from the provided data. During the training process, the model analyzes the data, identifies patterns, and adjusts its parameters to improve its accuracy and performance.
B. While training the model involves creating and refining its parameters, the model itself is not created during the training process. The model is typically created during the initial development phase and is then trained to improve its capabilities.
C. Training the model is a necessary step before making it available for use, but the primary purpose of training is to enhance the model's ability to make accurate predictions or classifications based on the provided data.
D. Training the model helps to strengthen its predictive capabilities by adjusting its parameters based on the data it is exposed to. Through training, the model becomes more accurate and effective in making predictions or classifications.
Discussion
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