A network operations team is considering using Mist's predictive analytics to automatically trigger remediation actions. They are concerned about the accuracy of predictions and the potential for unnecessary actions. What is the best way to implement predictive analytics in this context?

Use predictive analytics to generate alerts and recommendations, but require human approval before any automated action is taken.

Use predictive analytics only for reporting, without any action.

Enable fully automated remediation based on all predictions to maximize efficiency.

Disable predictive analytics and rely on reactive troubleshooting.

A network administrator is explaining to a colleague how Mist's machine learning models are trained. They want to emphasize that the models are continuously improved. Which statement best describes this process?

Mist uses a fixed dataset for training and does not incorporate new data.

Mist relies on administrators to manually update the models with new data.

Mist trains its models once and then deploys them without further updates.

Mist continuously collects data from customer networks and uses it to retrain and refine its models.

A network architect is explaining to a non-technical stakeholder how Mist AI uses machine learning to improve network performance. The stakeholder asks: 'How does Mist know what 'normal' looks like for our network?' Which answer is most accurate?

Mist requires administrators to manually define what is normal for their network.

Mist learns the baseline behavior of your network by analyzing historical data and comparing it to patterns from other networks.

Mist uses a generic baseline that is the same for all networks.

Mist uses a fixed set of rules to define what is normal for all networks.

A network manager wants to move toward a 'self-driving network' where the system can automatically remediate common issues without human intervention. They are concerned about maintaining control and avoiding unintended changes. Which approach best aligns with Juniper Mist's self-driving network capabilities?

Fully automate all network changes and disable human oversight to maximize efficiency.

Enable Mist's automated actions for well-understood issues, while keeping human approval for changes that could have broad impact.

Implement a separate third-party automation tool to handle all changes independently of Mist.

Use Mist only for monitoring and continue manual troubleshooting for all issues.

In the Juniper Mist cloud, what is the primary source of data used for training machine learning models?

Configuration files from third-party network management systems

Manually entered data from administrator surveys

Publicly available internet traffic data

Telemetry data collected from access points, switches, and clients

Juniper NetworksCertified Associate, Mist AI

Domain 1Objective 2

Machine Learning JN0-253 Practice Questions (Page 6)

Part of the Juniper Mist Cloud Fundamentals domain, which makes up ~19% of our current practice bank. Juniper Networks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~7–11 in this domain), expect 2–3 from this objective — we provide 31 practice questions to prepare you well beyond it. (estimate)

31questions here

7free pages

7concepts

Questions 26–30

26expert · hard
A network operations team is considering using Mist's predictive analytics to automatically trigger remediation actions. They are concerned about the accuracy of predictions and the potential for unnecessary actions. What is the best way to implement predictive analytics in this context?
Select an answer first
27application · medium
A network administrator is explaining to a colleague how Mist's machine learning models are trained. They want to emphasize that the models are continuously improved. Which statement best describes this process?
Select an answer first
28expert · hard
A network architect is explaining to a non-technical stakeholder how Mist AI uses machine learning to improve network performance. The stakeholder asks: 'How does Mist know what 'normal' looks like for our network?' Which answer is most accurate?
Select an answer first
29expert · hard
A network manager wants to move toward a 'self-driving network' where the system can automatically remediate common issues without human intervention. They are concerned about maintaining control and avoiding unintended changes. Which approach best aligns with Juniper Mist's self-driving network capabilities?
Select an answer first
30foundation · easy
In the Juniper Mist cloud, what is the primary source of data used for training machine learning models?
Select an answer first

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