A machine learning (ML) specialist is using the Amazon SageMaker DeepAR forecasting algorithm to train a model on CPU-based Amazon EC2 On-Demand instances. The model currently takes multiple hours to train. The ML specialist wants to decrease the training time of the model.
Which approaches will meet this requirement7 (SELECT TWO )
The best approaches to decrease the training time of the model are C and D, because they can improve the computational efficiency and parallelization of the training process. These approaches have the following benefits:
The other options are not effective or relevant, because they have the following drawbacks:
References:
2:How GPUs Accelerate Machine Learning Training | NVIDIA Developer Blog
3:DeepAR Forecasting Algorithm - Amazon SageMaker
4:Distributed Training - Amazon SageMaker
5:Managed Spot Training - Amazon SageMaker
6:Automatic Scaling - Amazon SageMaker
7:How the DeepAR Algorithm Works - Amazon SageMaker
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