07.11.2019 · This would require at least the 16gb types ( .xlarge) (full list of ML instance types available here ). Further, depending on how compute intensive your pre-processing is, and your desired pre-processing completion time, you can opt for a compute optimized instance ( c4, c5) to speed this up. For the training job, specifically:
For information on available Amazon SageMaker Notebook Instance types, see CreateNotebookInstance . Note For most use cases, you should use a ml.t3.medium. This is the default instance type for CPU-based SageMaker images, and is available as part of the AWS Free Tier . >> Fast launch instances types are optimized to start in under two minutes.
To change the instance type Choose the instance type. In Select instance, choose one of the fast launch instance types that are listed. Or to see all instance types, switch off Fast launch only. The list can be sorted by any column. After choosing a type, choose Save and continue .
SageMaker is a pay-for-usage model. There is no minimum fee for it. When we think about instances on SageMaker, it all starts with an EC2 instance. This ...
A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook. In a CreateNotebookInstance request, specify the type of ML ...
role – The AWS Identity and Access Management (IAM) role that SageMaker uses to perform tasks on your behalf (for example, reading training results, call model artifacts from Amazon S3, and writing training results to Amazon S3). instance_count and instance_type – The type and number of Amazon EC2 ML compute instances to use for model training.
Amazon SageMaker capability: Free Tier usage per month for the first 2 months: Studio notebooks, and On-demand notebook instances: 250 hours of ml.t3.medium instance on Studio notebooks OR 250 hours of ml.t2 medium instance or ml.t3.medium instance on on-demand notebook instances
Amazon SageMaker Free Tier ; Studio notebooks, and On-demand notebook instances, 250 hours of ml.t3.medium instance on Studio notebooks OR 250 hours of ml.t2 ...
The following list provides links to the Availability Zone tables for each AWS Region supported by SageMaker. Each linked table has a column for each Availability Zone in the Region. For each Availability Zone, the SageMaker components that support each instance type are shown. Availability Zone Tables US East (Ohio) us-east-2
instance_type ( str) – The type of EC2 instance to use for processing, for example, ‘ml.c4.xlarge’. entrypoint ( list[str]) – The entrypoint for the processing job (default: None). This is in the form of a list of strings that make a command.