Preparing the essential prerequisites
In this section, we will ensure that the following prerequisites are ready before proceeding with the hands-on solutions of this chapter:
- We have a service limit increase to run SageMaker training jobs using the
ml.p2.xlargeinstance (SageMaker Training) - We have a service limit increase to run SageMaker training jobs using the
ml.p2.xlargeinstance (SageMaker Managed Spot Training)
If you are wondering why we are using ml.p2.xlarge instances in this chapter, that’s because we are required to use one of the supported instance types for the Image Classification Algorithm, as shown in the following screenshot:
Figure 6.2 – EC2 Instance Recommendation for the image classification algorithm
As we can see, we can use ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, and ml.p3.16xlarge (at the time of writing) when running training jobs using the Image Classification Algorithm...
