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The Case For the Anti-Script: A Multifactor Analysis of Script Adherence

Balto

“The anti-script doesn’t mean that you should wing it on every call… what anti-script means is, think about a physical paper script and an agent who is reading it off word for word… you’re taking the most powerful part of the human out of the human.” Share on Twitter. Share on Facebook.

Scripts 52
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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning

Policy 3 – Attach AWSLambda_FullAccess , which is an AWS managed policy that grants full access to Lambda, Lambda console features, and other related AWS services.

Scripts 119
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Build a serverless voice-based contextual chatbot for people with disabilities using Amazon Bedrock

AWS Machine Learning

Use the least privilege principal to provide only the minimum set of permissions needed to run the application. For our application, run the following command: amplify add auth If you get the following message, you can ignore it: Auth has already been added to this project.

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Bring legacy machine learning code into Amazon SageMaker using AWS Step Functions

AWS Machine Learning

SageMaker runs the legacy script inside a processing container. SageMaker takes your script, copies your data from Amazon Simple Storage Service (Amazon S3), and then pulls a processing container. The SageMaker Processing job sets up your processing image using a Docker container entrypoint script.

Scripts 132
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Schedule your notebooks from any JupyterLab environment using the Amazon SageMaker JupyterLab extension

AWS Machine Learning

Migrating from interactive development on notebooks to batch jobs required you to copy code snippets from the notebook into a script, package the script with all its dependencies into a container, and schedule the container to run. In the following section, we show an example of using initialization scripts to install packages.

Scripts 84
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Build a cross-account MLOps workflow using the Amazon SageMaker model registry

AWS Machine Learning

The following code illustrates this policy, but don’t add it to the shared services account yet: #Data Science account's policy to access Shared Services' S3 bucket { 'Version': '2012-10-17', 'Statement': [{ 'Sid': 'AddPerm', 'Effect': 'Allow', 'Principal': { 'AWS': 'arn:aws:iam:: :root' }, "Action": [. 's3:PutObject',

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Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark

AWS Machine Learning

To make this solution scalable and customizable, we use Apache Spark’s distributed capabilities and PySpark’s flexible scripting capabilities. We use OpenSearch Serverless as a sample vector store and use the Llama 3.1 It requires IAM permission for OpenSearch Service Serverless.