AWS Machine Learning

AUGUST 31, 2023

One of the tools available as part of the ML governance is Amazon SageMaker Model Cards , which has the capability to create a single source of truth for model information by centralizing and standardizing documentation throughout the model lifecycle. They provide a fact sheet of the model that is important for model governance.

Government 98

Government Accountability Enterprise Engineering 98

AWS Machine Learning

MARCH 22, 2023

An AWS account with permissions to create AWS Identity and Access Management (IAM) policies and roles. Access and permissions to configure IDP to register Data Wrangler application and set up the authorization server or API. For data scientist: An S3 bucket that Data Wrangler can use to output transformed data.

APIs 79

APIs Engineering Analytics Scripts 79

AWS Machine Learning

MAY 8, 2023

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM).

APIs 70

APIs Government Accountability Scripts 70

AWS Machine Learning

FEBRUARY 1, 2024

This pipeline could be a batch pipeline if you prepare contextual data in advance, or a low-latency pipeline if you’re incorporating new contextual data on the fly. In the batch case, there are a couple challenges compared to typical data pipelines. He entered the big data space in 2013 and continues to explore that area.

Best practices 118

Best practices Engineering SaaS APIs 118

AWS Machine Learning

SEPTEMBER 6, 2023

The connector also ingests the access control list (ACL) information for each document. Solution overview In our solution, we configure AEM as a data source for an Amazon Kendra search index using the Amazon Kendra AEM connector. The connector also indexes the Access Control List (ACL) information for each message and document.

Management 103

Management Enterprise Analytics Finance 103

AWS Machine Learning

AUGUST 2, 2023

Amazon Kendra supports a variety of document formats , such as Microsoft Word, PDF, and text from various data sources. In this post, we focus on extending the document support in Amazon Kendra to make images searchable by their displayed content. This means you can manipulate and ingest your data as needed.

Enterprise 71

Enterprise Healthcare APIs Big data 71

AWS Machine Learning

JULY 29, 2022

It’s aligned with the AWS recommended practice of using temporary credentials to access AWS accounts. At the time of this writing, you can create only one domain per AWS account per Region. To implement the strong separation, you can use multiple AWS accounts with one domain per account as a workaround.

Management 74

Management APIs Accountability Construction 74

AWS Machine Learning

APRIL 24, 2023

Amazon Comprehend is a fully managed and continuously trained natural language processing (NLP) service that can extract insight about the content of a document or text. The steps are as follows: The client side calls Amazon API Gateway as the entry point to provide a client message as input. API Gateway bypasses the request to Lambda.

APIs 63

APIs Customer Experience Feedback Chatbots 63

AWS Machine Learning

DECEMBER 21, 2022

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Table formats provide a way to abstract data files as a table. You can also use the FeatureGroup().put_record

Scripts 73

Scripts Engineering APIs Big data 73

AWS Machine Learning

AUGUST 31, 2023

One of the tools available as part of the ML governance is Amazon SageMaker Model Cards , which has the capability to create a single source of truth for model information by centralizing and standardizing documentation throughout the model lifecycle. They provide a fact sheet of the model that is important for model governance.

Government 52

Government Accountability Enterprise Engineering 52

AWS Machine Learning

DECEMBER 1, 2022

In this post, we explore how companies can improve visibility into their models with centralized dashboards and detailed documentation of their models using two new features: SageMaker Model Cards and the SageMaker Model Dashboard. The Model dashboard is a centralized repository of all models that have been created in the account.

Government 79

Government Metrics APIs Engineering 79

AWS Machine Learning

MARCH 23, 2023

Applications and services can call the deployed endpoint directly or through a deployed serverless Amazon API Gateway architecture. To learn more about real-time endpoint architectural best practices, refer to Creating a machine learning-powered REST API with Amazon API Gateway mapping templates and Amazon SageMaker.

Scripts 101

Scripts APIs Government Analytics 101

AWS Machine Learning

JULY 19, 2022

Synchronous translation has limits on the document size it can translate; as of this writing, it’s set to 5,000 bytes. For larger document sizes, consider using an asynchronous route of creating the job using start_text_translation_job and checking the status via describe_text_translation_job. Prerequisites. Deploy the solution.

Engineering 84

Engineering APIs Education Best practices 84

AWS Machine Learning

SEPTEMBER 9, 2022

In the artificial intelligence (AI) space, athenahealth uses data science and machine learning (ML) to accelerate business processes and provide recommendations, predictions, and insights across multiple services. Each project maintained detailed documentation that outlined how each script was used to build the final model.

Engineering 75

Engineering Healthcare APIs Scripts 75

AWS Machine Learning

APRIL 19, 2023

This example notebook demonstrates the pattern of using Feature Store as a central repository from which data scientists can extract training datasets. In addition to creating a training dataset, we use the PutRecord API to put the 1-week feature aggregations into the online feature store nightly. Nov-01,22:01:00 1 74.99 …9843 99.50

Engineering 77

Engineering Analytics APIs Enterprise 77

AWS Machine Learning

SEPTEMBER 11, 2024

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously.

Benchmark 82

Benchmark Banking Analytics Big data 82

AWS Machine Learning

DECEMBER 1, 2022

They have a wide variety of personas to account for, each with their own unique sets of needs, and building the right sets of permissions policies to meet those needs can sometimes be an inhibitor to agility. You can change the existing policies here by selecting the policy and editing the document. Link the new role to a user.

Management 73

Management Government Enterprise APIs 73

AWS Machine Learning

JULY 21, 2022

You can also access the trial data via the Python SDK to generate your own visualization using your preferred plotting libraries. To learn more about Experiments APIs and SDKs, we recommend the following documentation: CreateExperiment and Amazon SageMaker Experiments Python SDK. Suggested readings.

Metrics 77

Metrics Scripts Enterprise Telecommunications 77

Nicereply

MAY 28, 2020

That might include a software version, account number or additional logs. The consistency problem can be avoided by defining all the categories rigorously in a shared document, mentioning each edge case, like the one above, to what category it should belong. Clean data. In general, the more training data you have, the better.

Customer Support 92

Customer Support APIs Big data Personalization 92

AWS Machine Learning

JANUARY 26, 2024

In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

Best practices 129

Best practices Government Engineering Accountability 129

Stratifyd

JANUARY 3, 2019

Key accountabilities & responsibilities. Maintain and develop Stratifyd’s API layer and/or analytics pipeline. Design, implement, and document new platform features and associated unit tests. and Python/C API. Experience and/or knowledge of AI, Big Data, Tech. Preferred Skills & Experience.

Engineering 40

Engineering APIs Analytics Healthcare 40

AWS Machine Learning

OCTOBER 23, 2024

This intuitive platform enables the rapid development of AI-powered solutions such as conversational interfaces, document summarization tools, and content generation apps through a drag-and-drop interface. The IDP solution uses the power of LLMs to automate tedious document-centric processes, freeing up your team for higher-value work.

Enterprise 66

Enterprise APIs Engineering Government 66

AWS Machine Learning

AUGUST 2, 2024

The Product Stewardship department is responsible for managing a large collection of regulatory compliance documents. Example questions might be “What are the restrictions for CMR substances?”, “How long do I need to keep the documents related to a toluene sale?”, or “What is the reach characterization ratio and how do I calculate it?”

APIs 98

APIs Analytics Chatbots Engineering 98

AWS Machine Learning

SEPTEMBER 21, 2022

Until recently, organizations hosting private AWS DeepRacer events had to create and assign AWS accounts to every event participant. This often meant securing and monitoring usage across hundreds or even thousands of AWS accounts. Build a solution around AWS DeepRacer multi-user account management.

Accountability 62

Accountability APIs Enterprise Big data 62