A. Add labels over time to indicate which engine faults occur at what time in the future to turn this into a supervised learning problem. Use a recurrent neural network (RNN) to train the model to recognize when an engine might need maintenance for a certain fault.
B. This data requires an unsupervised learning algorithm. Use Amazon SageMaker k-means to cluster the data.
C. Add labels over time to indicate which engine faults occur at what time in the future to turn this into a supervised learning problem. Use a convolutional neural network (CNN) to train the model to recognize when an engine might need maintenance for a certain fault.
D. This data is already formulated as a time series. Use Amazon SageMaker seq2seq to model the time series.
- Trademarks, certification & product names are used for reference only and belong to Amazon.
Join the Discussion
You must be logged in to post a comment.