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Question 54 - Professional Machine Learning Engineer discussion

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You work for a large technology company that wants to modernize their contact center. You have been asked to develop a solution to classify incoming calls by product so that requests can be more quickly routed to the correct support team. You have already transcribed the calls using the Speech-to-Text API. You want to minimize data preprocessing and development time. How should you build the model?

A.
Use the Al Platform Training built-in algorithms to create a custom model
Answers
A.
Use the Al Platform Training built-in algorithms to create a custom model
B.
Use AutoML Natural Language to extract custom entities for classification
Answers
B.
Use AutoML Natural Language to extract custom entities for classification
C.
Use the Cloud Natural Language API to extract custom entities for classification
Answers
C.
Use the Cloud Natural Language API to extract custom entities for classification
D.
Build a custom model to identify the product keywords from the transcribed calls, and then run the keywords through a classification algorithm
Answers
D.
Build a custom model to identify the product keywords from the transcribed calls, and then run the keywords through a classification algorithm
Suggested answer: B

Explanation:

AutoML Natural Language is a service that allows users to create custom natural language models using their own data and labels. It supports various natural language tasks, such as text classification, entity extraction, and sentiment analysis. AutoML Natural Language can be used to build a model to classify incoming calls by product, as it can extract custom entities from the transcribed calls and assign them to predefined categories. AutoML Natural Language also minimizes data preprocessing and development time, as it handles the data preparation, model training, and evaluation automatically. The other options are not as suitable for this scenario. AI Platform Training built-in algorithms are a set of pre-defined algorithms that can be used to train ML models on AI Platform, but they do not support natural language processing tasks. Cloud Natural Language API is a pre-trained service that provides natural language understanding capabilities, such as sentiment analysis, entity analysis, syntax analysis, and content classification. However, it does not support custom entities or categories, and may not recognize the product names from the calls. Building a custom model to identify the product keywords and then running them through a classification algorithm would require more data preprocessing and development time, as well as more coding and testing.Reference:

AutoML Natural Language documentation

AI Platform Training built-in algorithms documentation

Cloud Natural Language API documentation

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asked 18/09/2024
Jorge Correa
40 questions
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