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Answer: Utilize the Cloud Natural Language API in the application and process the generated Entity Analysis as labels.
The Cloud Natural Language API offers a pre-trained machine learning model capable of performing entity analysis, among other natural language processing tasks. Its Entity Analysis feature can automatically identify and extract relevant subject labels from text, providing a swift and straightforward solution that doesn't require additional development or machine learning expertise. Sentiment Analysis (Option B) focuses on the text's tone and may not be ideal for generating subject labels. Options A and C involve developing and training a text classification model with TensorFlow, which may not be practical given the constraints of limited developer resources and the urgency to implement the feature quickly.
Author: LeetQuiz Editorial Team
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When developing a Google Cloud application that requires automatic generation of subject labels for users' blog posts under tight deadlines and without additional developer resources or machine learning expertise, what is the most suitable approach?
A
Develop and train a text classification model using TensorFlow, deploy it using Cloud Machine Learning Engine, call the model from the application, and process the results as labels.
B
Utilize the Cloud Natural Language API in the application and process the generated Sentiment Analysis as labels.
C
Develop and train a text classification model using TensorFlow, deploy it using a Kubernetes Engine cluster, call the model from the application, and process the results as labels.
D
Utilize the Cloud Natural Language API in the application and process the generated Entity Analysis as labels.
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