MLS-C01 · Question #27
MLS-C01 Question #27: Real Exam Question with Answer & Explanation
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Question
A company's Machine Learning Specialist needs to improve the training speed of a time-series forecasting model using TensorFlow. The training is currently implemented on a single-GPU machine and takes approximately 23 hours to complete. The training needs to be run daily. The model accuracy is acceptable, but the company anticipates a continuous increase in the size of the training data and a need to update the model on an hourly, rather than a daily, basis. The company also wants to minimize coding effort and infrastructure changes. What should the Machine Learning Specialist do to the training solution to allow it to scale for future demand?
Options
- ADo not change the TensorFlow code. Change the machine to one with a more powerful GPU to
- BChange the TensorFlow code to implement a Horovod distributed framework supported by
- CSwitch to using a built-in AWS SageMaker DeepAR model. Parallelize the training to as many
- DMove the training to Amazon EMR and distribute the workload to as many machines as needed to
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