A company is building custom deep learning models in Amazon SageMaker by using training and inference containers that run on Amazon EC2 instances.The company wants to reduce training costs but does not want to change the current architecture.The SageMaker training job can finish after interruptions.The company can wait days for the results.
Which combination of resources should the company use to meet these requirements MOST cost-effectively?
(Choose two.)
On-Demand Instances
Checkpoints
Reserved Instances
Incremental training
Spot instances
I deduce that the answer is:
Checkpoints