Question 93:
You work as a machine learning specialist on a team tasked with designing an image recognition system that can quickly adapt to new observations. Your team is designing automated driving software for cars in a ride-share fleet. Your company wants to implement a service where when users hail a ride through your app on their mobile device. A nearby self-driving car arrives at the user’s location. It has the desired route preloaded and is ready to take the user to their destination. Your team has decided to use the SageMaker Image Classification algorithm in your image recognition model. The machine learning models powering this self-driving car fleet need to react very quickly to new observations, such as previously not encountered obstacles like different types and sized animals, etc. Which hyperparameter would you set, and to what value, to obtain the desired outcome?
Answer options:
A.early_stopping set to True B.early_stopping set to False C.learning_rate set to 0.1 D.learning_rate set to 0.8 E.use_pretrained_model set to 0 F.use_pretrained_model set to 1