AWS Machine Learning

APRIL 11, 2023

One important aspect of this foundation is to organize their AWS environment following a multi-account strategy. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs.

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APIs Accountability Scripts Enterprise 81

AWS Machine Learning

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts. Mitigation strategies : Implementing measures to minimize or eliminate risks.

Government 90

Government Management APIs Accountability 90

AWS Machine Learning

FEBRUARY 29, 2024

This enables data scientists to quickly build and iterate on ML models, and empowers ML engineers to run through continuous integration and continuous delivery (CI/CD) ML pipelines faster, decreasing time to production for models. You can then iterate on preprocessing, training, and evaluation scripts, as well as configuration choices.

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Scripts Engineering Metrics Best practices 117

AWS Machine Learning

JULY 11, 2024

Agents for Amazon Bedrock automates the prompt engineering and orchestration of user-requested tasks. This solution uses Retrieval Augmented Generation (RAG) to ensure the generated scripts adhere to organizational needs and industry standards. A GitHub account with a repository to store the generated Terraform scripts.

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Scripts APIs Engineering industry standards 130

AWS Machine Learning

AUGUST 1, 2024

By demonstrating the process of deploying fine-tuned models, we aim to empower data scientists, ML engineers, and application developers to harness the full potential of FMs while addressing unique application requirements. Amazon Bedrock service starts an import job in an AWS operated deployment account.

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APIs Scripts Real estate Accountability 123

AWS Machine Learning

NOVEMBER 9, 2023

Central model registry – Amazon SageMaker Model Registry is set up in a separate AWS account to track model versions generated across the dev and prod environments. Approve the model in SageMaker Model Registry in the central model registry account. Create a pull request to merge the code into the main branch of the GitHub repository.

Scripts 124

Scripts Accountability Best practices Engineering 124

AWS Machine Learning

JULY 2, 2024

An Amazon OpenSearch Serverless vector engine to store enterprise data as vectors to perform semantic search. Amazon Bedrock retrieves relevant data from the vector store (using the vector engine for OpenSearch Serverless ) using hybrid search. Create an S3 bucket in your account. The following diagram illustrates this workflow.

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AWS Machine Learning

OCTOBER 21, 2024

If you have a different format, you can potentially use Llama convert scripts or Mistral convert scripts to convert your model to a supported format. The fine-tuning scripts are based on the scripts provided by the Llama fine-tuning repository. The default import quota for each account is three models.

APIs 139

APIs Scripts Finance Real estate 139

AWS Machine Learning

JUNE 16, 2023

They had several skilled engineers and scientists building insightful models that improved the quality of risk analysis on their platform. SambaSafety’s data science team maintained several script-like artifacts as part of their development workflow. SambaSafety connected with AWS account teams with their problem.

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Scripts Engineering Accountability Consulting 98

AWS Machine Learning

MARCH 15, 2023

We demonstrate how two different personas, a data scientist and an MLOps engineer, can collaborate to lift and shift hundreds of legacy models. SageMaker runs the legacy script inside a processing container. We assume the involvement of two personas: a data scientist and an MLOps engineer.

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Scripts APIs Engineering Construction 136

Aspect

MAY 2, 2018

It also has to be engineered to fit different purposes and contexts. No, there are simple, static bots that can be developed with scripting tools. These bots allow for conversation branching and connection to structured data sources such as account balances. appeared first on Aspect Blogs.

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Engineering Chatbots Scripts Sales 76

AWS Machine Learning

SEPTEMBER 20, 2023

SageMaker Studio allows data scientists, ML engineers, and data engineers to prepare data, build, train, and deploy ML models on one web interface. SageMaker is a comprehensive ML service enabling business analysts, data scientists, and MLOps engineers to build, train, and deploy ML models for any use case, regardless of ML expertise.

Scripts 124

Scripts Engineering Accountability Enterprise 124

AWS Machine Learning

OCTOBER 29, 2024

Financial services firms can accelerate workflows around loan applications, account openings, and regulatory reporting. This will trigger the AWS CloudFormation template in your AWS account. For manufacturers, this means streamlining processes like purchase order management, invoice processing, and supply chain documentation.

Finance 107

Finance Enterprise Healthcare Scripts 107

AWS Machine Learning

JUNE 4, 2024

The workflow includes the following steps: The user runs the terraform apply The Terraform local-exec provisioner is used to run a Python script that downloads the public dataset DialogSum from the Hugging Face Hub. Prerequisites This solution requires the following prerequisites: An AWS account.

Scripts 132

Scripts Accountability Engineering Best practices 132

AWS Machine Learning

JUNE 21, 2023

Lifecycle configurations are shell scripts triggered by Studio lifecycle events, such as starting a new Studio notebook. This enables you to apply DevOps best practices and meet safety, compliance, and configuration standards across all AWS accounts and Regions. For Windows, use.cdk-venv/Scripts/activate.bat.

Construction 98

Construction Scripts Engineering Accountability 98

AWS Machine Learning

OCTOBER 18, 2024

AI Hub offers automatic conversion and optimization of PyTorch or ONNX models for efficient on-device deployment using TensorFlow Lite, ONNX Runtime, or Qualcomm AI Engine Direct SDK. An AWS account. Make sure your account has the SageMaker Training resource type limit for ml.g5.2xlarge increased to 1 using the Service Quotas console.

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Scripts APIs Engineering Marketing 99

AWS Machine Learning

NOVEMBER 30, 2023

Solution overview To deploy your SageMaker HyperPod, you first prepare your environment by configuring your Amazon Virtual Private Cloud (Amazon VPC) network and security groups, deploying supporting services such as FSx for Lustre in your VPC, and publishing your Slurm lifecycle scripts to an S3 bucket. Choose Create role. Choose Save.

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Scripts Engineering Government Management 128

AWS Machine Learning

DECEMBER 22, 2023

The agent can assist users with finding their account information, completing a loan application, or answering natural language questions while also citing sources for the provided answers. This memory allows the agent to provide responses that take into account the context of the ongoing conversation.

Scripts 124

Scripts Chatbots Accountability Multi-channel support 124

AWS Machine Learning

NOVEMBER 13, 2024

script to automatically copy the cdk configuration parameters to a configuration file by running the following command, still in the /cdk folder: /scripts/postdeploy.sh After the deployment is complete, you have two options. The preferred option is to use the provided postdeploy.sh

APIs 121

APIs Scripts Accountability Entertainment 121

AWS Machine Learning

JULY 11, 2024

Use prompt engineering to provide this additional context to the LLM along with the original question. Prerequisites For this walkthrough, you should have the following prerequisites: An AWS account set up. If you have administrator access to the account, no additional action is required. expand(token_embeddings.size()).float()

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Scripts Accountability APIs Engineering 125

AWS Machine Learning

JULY 25, 2024

Overview of solution This post presents the steps to create a certificate and private key, configure Azure AD (either using the Azure AD console or a PowerShell script), and configure Amazon Q Business. You need a Microsoft Windows instance to run PowerShell scripts and commands with PowerShell 7.4.1+. Choose New registration.

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Scripts APIs Engineering Enterprise 105

AWS Machine Learning

MARCH 8, 2023

After the data is downloaded into the training instance, the custom training script performs data preparation tasks and then trains the ML model using the XGBoost Estimator. Store your Snowflake account credentials in AWS Secrets Manager. Ingest the data in a table in your Snowflake account. amazonaws.com/sagemaker-xgboost:1.5-1

Scripts 129

Scripts Accountability Enterprise Management 129

AWS Machine Learning

AUGUST 29, 2023

This architecture design represents a multi-account strategy where ML models are built, trained, and registered in a central model registry within a data science development account (which has more controls than a typical application development account).

Scripts 85

Scripts APIs Enterprise Accountability 85

AWS Machine Learning

JUNE 19, 2024

Prerequisites You need an AWS account and an AWS Identity and Access Management (IAM) role and user with permissions to create and manage the necessary resources and components for this application. If you don’t have an AWS account, see How do I create and activate a new Amazon Web Services account?

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APIs Engineering Accountability Scripts 127

AWS Machine Learning

SEPTEMBER 23, 2024

Throughout this exercise, you use Amazon Q Developer in SageMaker Studio for various stages of the development lifecycle and experience firsthand how this natural language assistant can help even the most experienced data scientists or ML engineers streamline the development process and accelerate time-to-value. Choose Create configuration.

Engineering 85

Engineering Scripts Automotive Advertising 85

AWS Machine Learning

NOVEMBER 1, 2024

Each step became an independent stream, so our engineers could iteratively develop and evaluate the performance and speed until they worked well in isolation. The FM resides in a separate AWS account and virtual private cloud (VPC) from the backend services. Generate and invoke private API calls.

APIs 109

APIs Scripts Engineering Government 109

AWS Machine Learning

DECEMBER 21, 2022

Amazon SageMaker Feature Store is a purpose-built feature management solution that helps data scientists and ML engineers securely store, discover, and share curated data used in training and prediction workflows. The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account.

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Scripts Engineering APIs Big data 85

AWS Machine Learning

FEBRUARY 14, 2024

Prerequisites For this walkthrough, you should have the following prerequisites: Familiarity with SageMaker Ground Truth labeling jobs and the workforce portal Familiarity with the AWS Cloud Development Kit (AWS CDK) An AWS account with the permissions to deploy the AWS CDK stack A SageMaker Ground Truth private workforce Python 3.9+

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Scripts Engineering Entertainment Healthcare 127

AWS Machine Learning

SEPTEMBER 18, 2024

Reusable scaling scripts for rapid experimentation – HyperPod offers a set of scalable and reusable scripts that simplify the process of launching multiple training runs. In your account, you will have a VPC provisioned with a public and private subnet, and an S3 bucket synced to your FSxL file system via a data repository link.

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Scripts Metrics Management Accountability 112

AWS Machine Learning

NOVEMBER 20, 2023

Data scientists or ML engineers who want to run model training can do so without the burden of configuring training infrastructure or managing Docker and the compatibility of different libraries. We reviewed the training script code to see if anything was causing the CPU bottleneck. 24xlarge instances. region_name}.amazonaws.com/pytorch-training:2.0.0-gpu-py310-cu118-ubuntu20.04-sagemaker'

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Scripts Finance Telecommunications Enterprise 117

AWS Machine Learning

AUGUST 10, 2023

As recommended by AWS as a best practice , customers have used separate accounts to simplify policy management for users and isolate resources by workloads and account. SageMaker services, such as Processing, Training, and Hosting, collect metrics and logs from the running instances and push them to users’ Amazon CloudWatch accounts.

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Scripts Accountability Metrics Best practices 90

AWS Machine Learning

JULY 25, 2024

eks-5e0fdde Install the required AWS Identity and Access Management (IAM) role for the service account and the node problem detector plugin. In the training scripts, it saves checkpoints periodically so that the training will resume from the previous checkpoint. Ziwen Ning is a software development engineer at AWS. /install.sh

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Construction Metrics Scripts Engineering 114

AWS Machine Learning

NOVEMBER 15, 2023

Prerequisites The following are prerequisites for completing the walkthrough in this post: An AWS account Familiarity with SageMaker concepts, such as an Estimator, training job, and HPO job Familiarity with the Amazon SageMaker Python SDK Python programming knowledge Implement the solution The full code is available in the GitHub repo.

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Scripts Best practices Accountability Engineering 112

AWS Machine Learning

MAY 22, 2024

Customers can more easily locate products that have correct descriptions, because it allows the search engine to identify products that match not just the general category but also the specific attributes mentioned in the product description. For details, see Creating an AWS account. We use Amazon SageMaker Studio with the ml.t3.medium

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Scripts Engineering Accountability Benchmark 131

AWS Machine Learning

APRIL 11, 2023

As long as a user has access to the AWS account, Studio domain ID, and user profile, they can access the link. Next the script will install packages iproute and jq , which will be used in the following step. Next the script will install packages iproute and jq , which will be used in the following step. sh setup.sh sh setup.sh

Scripts 88

Scripts Automotive Engineering Healthcare 88

AWS Machine Learning

NOVEMBER 15, 2024

For early detection, implement custom testing scripts that run toxicity evaluations on new data and model outputs continuously. Integrating scheduled toxicity assessments and custom testing scripts into your development pipeline helps you continuously monitor and adjust model behavior.

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APIs Government Best practices Metrics 90

AWS Machine Learning

APRIL 26, 2024

Also make sure you have the account-level service limit for using ml.p4d.24xlarge user Write a Python script to read a CSV file containing stock prices and plot the closing prices over time using Matplotlib. The file should have columns named 'Date' and 'Close' for this script to work correctly. 24xlarge or ml.pde.24xlarge

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Transportation Scripts Accountability Benchmark 124