00:01In Lesson 2, you laid the groundwork for the MoodTracker app by implementing the basic UI for emotion detection. In this demo, you’ll go through the process of integrating the Core ML model into your MoodTracker app to perform emotion detection on images. This includes setting up a view model, configuring the classifier, and updating the user interface to display the results.
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This content was released on Sep 18 2024. The official support period is 6-months
from this date.
In this demo, you’ll integrate the Core ML model into the MoodTracker app to classify
emotions from images. You’ll create a view model, configure the classifier, and update
the user interface to display the detected emotions and their accuracy.
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