AWS Machine Learning

AUGUST 17, 2023

Option B: Use a SageMaker Processing job with Spark In this option, we use a SageMaker Processing job with a Spark script to load the original dataset from Amazon Redshift, perform feature engineering, and ingest the data into SageMaker Feature Store. The environment preparation process may take some time to complete.

APIs 86

APIs Engineering Scripts Analytics 86

AWS Machine Learning

DECEMBER 1, 2022

However, if you want to update existing resources to facilitate resource isolation, administrations can use the add-tag SageMaker API call in a script. Since the launch of the multi-domain capability, new resources are automatically tagged with aws:ResourceTag/sagemaker:domain-arn. experiments=`aws --region $REGION.

APIs 76

APIs Engineering Scripts Accountability 76

AWS Machine Learning

MARCH 7, 2023

When you open a notebook in Studio, you are prompted to set up your environment by choosing a SageMaker image, a kernel, an instance type, and, optionally, a lifecycle configuration script that runs on image startup. The main benefit is that a data scientist can choose which script to run to customize the container with new packages.

Management 86

Management Scripts Government Engineering 86

AWS Machine Learning

JUNE 6, 2023

Run your DLC container with a model training script to fine-tune the RoBERTa model. After model training is complete, package the saved model, inference scripts, and a few metadata files into a tar file that SageMaker inference can use and upload the model package to an Amazon Simple Storage Service (Amazon S3) bucket.

Scripts 81

Scripts APIs Benchmark Management 81

AWS Machine Learning

NOVEMBER 23, 2022

Complete the following steps: Download the bootstrap script from s3://emr-data-access-control- /customer-bootstrap-actions/gcsc/replace-rpms.sh , replacing region with your region. Your Studio user’s execution role needs to be updated to allow the GetClusterSessionCredentials API action. SNAPSHOT20221121212949.noarch.rpm. noarch.rpm.

Scripts 90

Scripts APIs Engineering Sales 90

AWS Machine Learning

JUNE 28, 2022

The input data is a multi-variate time series that includes hourly electricity consumption of 321 users from 2012–2014. JumpStart features aren’t available in SageMaker notebook instances, and you can’t access them through SageMaker APIs or the AWS Command Line Interface (AWS CLI). Launch the solution.

Metrics 88

Metrics Healthcare Transportation Accountability 88

Nexmo

FEBRUARY 14, 2020

In this tutorial, we’ll use a Nexmo Voice number to create a callback script that interacts with a caller to prompt for a voice message. Though the built-in web server should not be used in a production environment, it is fine for sample scripts like this. Make sure to replace {bucket_name} with the actual bucket name.

Scripts 120

Scripts Accountability APIs Management 120

AWS Machine Learning

DECEMBER 14, 2023

After you stop the Space, you can modify its settings using either the UI or API via the updated SageMaker Studio interface and then restart the Space. This setup enables you to centrally store notebooks, scripts, and other project files, accessible across all your SageMaker Studio sessions and instances.

APIs 123

APIs Engineering Management Scripts 123

AWS Machine Learning

JANUARY 9, 2023

Amazon Kendra Intelligent Ranking application programming interface (API) – The functions from this API are used to perform tasks related to provisioning execution plans and semantic re-ranking of your search results. Create and start OpenSearch using the Quickstart script. Download the search_processing_kendra_quickstart.sh

Scripts 98

Scripts APIs Engineering Transportation 98

AWS Machine Learning

APRIL 23, 2024

You can run the script by choosing Run in Code Editor or using the CLI in a JupyterLab terminal. The only way to access and interact with Docker images is via the exposed Docker API operations. LCCs are scripts that SageMaker runs during events like space creation. API version: 1.41 (downgraded from 1.43) Go version: go1.20.10

Scripts 121

Scripts Engineering APIs Feedback 121

AWS Machine Learning

SEPTEMBER 7, 2023

You can then use a script (process.py) to work on a specific portion of the data based on the instance number and the corresponding element in the list of items. if there are multiple, you can fetch available pipelines using boto3 api #and trigger the appropriate one based on your logic. 1", instance_type="ml.m5.xlarge",

Best practices 119

Best practices Scripts Construction APIs 119