CLF-C02 Question 246
Select 2A company wants to build a chatbot to handle customer inquiries in natural language and also needs a solution to train and deploy machine learning models for sales predictions. Which combination of AWS services should they use?
- A
Amazon Lex
- B
Amazon SageMaker
- C
Amazon Kendra
- D
Amazon Rekognition
- E
AWS Lambda
Show answer and explanation
Correct answers: A, B
Explanation
The company needs two distinct capabilities: natural language understanding for a chatbot and a solution to train and deploy machine learning models. Amazon Lex is ideal for creating the chatbot, as it handles natural language interactions. Amazon SageMaker is the best choice for training and deploying ML models for predictions. Together, these services meet both requirements efficiently.
- A. Correct.
Amazon Lex is the correct choice for building a chatbot that can handle customer inquiries in natural language. It provides natural language understanding and automatic speech recognition capabilities.
- B. Correct.
Amazon SageMaker is the correct choice for training and deploying machine learning models, such as those for sales predictions. It offers a fully managed service for building, training, and deploying ML models.
- C. Incorrect.
Amazon Kendra is not suitable for this use case because it is designed for intelligent search solutions across enterprise data, not for chatbots or training ML models.
- D. Incorrect.
Amazon Rekognition is not applicable here, as it is used for image and video analysis, such as facial recognition and object detection, which are unrelated to this scenario.
- E. Incorrect.
AWS Lambda, while a powerful compute service for running code without provisioning servers, is not specifically used for building chatbots or training ML models. It may complement these services but is not directly relevant to the question.