Google Professional Machine Learning Engineer Question 51
Select 3Google Cloud PlatformYou are a Machine Learning Engineer tasked with building a conversational AI solution for a customer support chatbot. The chatbot should respond seamlessly to customer queries about product details, order status, and return policies. You decide to use Google Cloud's Agent Builder to create this solution. Which of the following steps are necessary to build and deploy the chatbot using Agent Builder?
- A
Define and import intents that capture user queries and map them to appropriate responses.
- B
Manually build a custom Natural Language Processing (NLP) model for the chatbot.
- C
Integrate the chatbot with communication platforms like Google Chat or Slack using Agent Builder.
- D
Test the chatbot and iteratively refine its responses based on user interactions.
- E
Deploy the chatbot to production using Cloud Run or Kubernetes Engine.
Show answer and explanation
Correct answers: A, C, D
Explanation
Agent Builder simplifies the process of creating conversational AI solutions by leveraging Dialogflow's prebuilt NLP capabilities, enabling integration with communication platforms, and providing tools for testing and refinement. Manual NLP model building and external deployment steps are not required, as Agent Builder provides these functionalities out of the box.
- A. Correct.
Correct: Defining and importing intents is a critical step in Agent Builder as it enables the chatbot to understand and appropriately respond to user queries.
- B. Incorrect.
Incorrect: Agent Builder uses Dialogflow's prebuilt NLP capabilities, so there is no need to manually build a custom NLP model.
- C. Correct.
Correct: Agent Builder supports integration with various communication platforms, making it easier to make the chatbot accessible to end users.
- D. Correct.
Correct: Testing and refining the chatbot ensures it provides accurate and helpful responses to users, which is a best practice in building conversational agents.
- E. Incorrect.
Incorrect: Agent Builder automatically handles deployment through its managed services, so manual deployment using Cloud Run or Kubernetes Engine is unnecessary.