Google Professional Machine Learning Engineer Question 53
Select 3Google Cloud PlatformYou are tasked with creating a conversational AI chatbot for a customer service application using Google Cloud's Agent Builder. The chatbot should handle customer inquiries about order status and delivery issues efficiently while scaling to support a high volume of users. Which of the following steps are essential for ensuring the chatbot meets the requirements?
- A
Design intents and entities that align with the common user queries related to order status and delivery.
- B
Use Google Cloud's BigQuery to store and train the agent's conversation data.
- C
Enable integration with live agents for handling complex or unresolved queries.
- D
Leverage Dialogflow CX's flow builder feature to create robust conversation paths.
- E
Configure the chatbot to directly call a pre-trained TensorFlow model for making predictions.
Show answer and explanation
Correct answers: A, C, D
Explanation
To create an effective chatbot with Agent Builder, it is critical to design intents and entities that address user needs, use tools like Dialogflow CX to structure conversations, and provide fallback options such as live agent integration for unresolved queries. These steps ensure the chatbot is efficient, scalable, and customer-centric.
- A. Correct.
Correct: Designing intents and entities to align with user queries ensures the chatbot understands and responds appropriately to common customer questions.
- B. Incorrect.
Incorrect: BigQuery is primarily used for data storage and analytics, not for directly building or training conversational agents.
- C. Correct.
Correct: Integration with live agents is essential for handling complex or unresolved queries, ensuring better customer satisfaction.
- D. Correct.
Correct: Dialogflow CX's flow builder allows you to design structured conversation paths, which is crucial for efficiently handling user inquiries.
- E. Incorrect.
Incorrect: While TensorFlow models can be useful for advanced predictions, they are not directly relevant to the core functionality of an Agent Builder chatbot.