AWS Machine Learning

AUGUST 13, 2024

The healthcare industry generates and collects a significant amount of unstructured textual data, including clinical documentation such as patient information, medical history, and test results, as well as non-clinical documentation like administrative records. Lastly, the Lambda function stores the question list in Amazon S3.

Healthcare 126

Healthcare APIs Consulting Consulting 126

AWS Machine Learning

NOVEMBER 29, 2023

Amazon SageMaker notebook jobs allow data scientists to run their notebooks on demand or on a schedule with a few clicks in SageMaker Studio. With this launch, you can programmatically run notebooks as jobs using APIs provided by Amazon SageMaker Pipelines , the ML workflow orchestration feature of Amazon SageMaker.

APIs 101

APIs Management Engineering Big data 101

AWS Machine Learning

FEBRUARY 29, 2024

Knowledge Bases for Amazon Bedrock automates synchronization of your data with your vector store, including diffing the data when it’s updated, document loading, and chunking, as well as semantic embedding. RAG is a popular technique that combines the use of private data with large language models (LLMs).

APIs 131

APIs Healthcare Scripts Enterprise 131

AWS Machine Learning

JUNE 19, 2024

Imagine the possibilities: Quick and efficient brainstorming sessions, real-time ideation, and even drafting documents or code snippets—all powered by the latest advancements in AI. The Slack application sends the event to Amazon API Gateway , which is used in the event subscription.

APIs 96

APIs Engineering Accountability Big data 96

AWS Machine Learning

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

APIs 115

APIs Enterprise Big data Chatbots 115

AWS Machine Learning

JUNE 12, 2024

This solution uses an Amazon Cognito user pool as an OAuth-compatible identity provider (IdP), which is required in order to exchange a token with AWS IAM Identity Center and later on interact with the Amazon Q Business APIs. Amazon Q uses the chat_sync API to carry out the conversation.

APIs 128

APIs Enterprise Accountability Feedback 128

Avaya

NOVEMBER 16, 2016

Open APIs: An open API model is advantageous in that it allows developers outside of companies to easily access and use APIs to create breakthrough innovations. At the same time, however, publicly available APIs are also exposed ones. billion GB of data were being produced every day in 2012 alone!)

APIs 72

APIs Transportation Enterprise Healthcare 72

AWS Machine Learning

MARCH 22, 2023

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. Select the configuration that starts the process of registering Data Wrangler as an application.

APIs 91

APIs Engineering Analytics Scripts 91

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 117

Management Enterprise Analytics Finance 117

AWS Machine Learning

NOVEMBER 27, 2023

Most real-world data exists in unstructured formats like PDFs, which requires preprocessing before it can be used effectively. According to IDC , unstructured data accounts for over 80% of all business data today. This includes formats like emails, PDFs, scanned documents, images, audio, video, and more.

Engineering 89

Engineering APIs Big data Accountability 89

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 131

Best practices Engineering SaaS APIs 131

AWS Machine Learning

DECEMBER 21, 2022

SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Customers can also access offline store data using a Spark runtime and perform big data processing for ML feature analysis and feature engineering use cases. Table formats provide a way to abstract data files as a table.

Scripts 84

Scripts Engineering APIs Big data 84

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. Both these features are available at no additional charge to SageMaker customers.

Government 91

Government Metrics APIs Engineering 91

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 113

Scripts APIs Government Analytics 113

AWS Machine Learning

JULY 19, 2023

Large language models (LLMs) can be used to analyze complex documents and provide summaries and answers to questions. The post Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data describes how to fine-tune an LLM using your own dataset.

Construction 71

Construction APIs Big data Engineering 71

AWS Machine Learning

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud.

Finance 120

Finance APIs Analytics Big data 120

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 111

Government Accountability Enterprise Best practices 111

AWS Machine Learning

JULY 29, 2022

Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to build, train, and deploy machine learning (ML) models quickly. The SageMaker Python SDK provides open-source APIs and containers to train and deploy models on SageMaker, using several different ML and deep learning frameworks.

Scripts 94

Scripts APIs Big data Engineering 94

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). Adds an IAM authorizer.

APIs 81

APIs Government Accountability Scripts 81

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 82

Enterprise Healthcare APIs Big data 82

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.

Customer Experience 70

Customer Experience APIs Feedback Chatbots 70

AWS Machine Learning

JULY 29, 2022

The solution also uses SAML attribute mapping to populate the SAML assertion with specific access-relevant data, such as user ID and user team. Because the solution creates a SAML API, you can use any IdP supporting SAML assertions to create this architecture. The API Gateway calls an SAML backend API. Custom SAML 2.0

Management 85

Management APIs Accountability Construction 85

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.

Engineering 94

Engineering APIs Education Best practices 94

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 88

Engineering Analytics APIs Enterprise 88

Spearline

JANUARY 23, 2018

” How about full endpoint documentation for all our products. An API (Application Programming Interface) will enhance your utilisation of our platform. But that’s not all… 2018 is going to be The Year of Data Analysis! Big data is here and we have plenty of it.

Benchmark 40

Benchmark Call flow APIs Big data 40

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 87

Engineering Healthcare APIs Scripts 87

AWS Machine Learning

JULY 25, 2022

For detailed instructions on how to use the DGL-KE, refer to Training knowledge graph embeddings at scale with the Deep Graph Library and DGL-KE Documentation. For production, we wanted to invoke the model as a simple API call. Packaging the solution as a scalable workflow. We used SageMaker notebooks to develop and debug our code.

Scripts 82

Scripts Engineering Analytics APIs 82

Nicereply

MAY 28, 2020

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

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 93

Benchmark Banking Analytics Big data 93

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.

Metrics 89

Metrics Scripts Enterprise Telecommunications 89

AWS Machine Learning

DECEMBER 1, 2022

You can change the existing policies here by selecting the policy and editing the document. This role can also be recreated via Infrastructure as Code (IaC) by simply taking the contents of the policy documents and inserting them into your existing solution. Link the new role to a user.

Management 84

Management Government Enterprise APIs 84

Xaqt

JUNE 22, 2020

Despite significant advancements in big data and open source tools, niche Contact Center Business Intelligence providers are still wed to their own proprietary tools leaving them saddled with technical debt and an inability to innovate from within. By putting it into the public domain, we invite your feedback and contributions.

Call Center 52

Call Center Contact Center Analytics Engineering 52

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 Best practices 52

Quadient

JULY 21, 2022

Hoewel ze zijn geëvolueerd van gedrukte naar een meer document-centrisch wereldbeeld, hebben ze de neiging om CCM in de eerste plaats te zien als gestructureerde, uitgaande communicatie die wordt aangedreven door wettelijke normen. Investeringen in CCM worden gedaan door on-premise, gelicentieerde software aan te schaffen.

Customer Experience 40

Customer Experience Management Journey mapping APIs 40

Dialer 360

DECEMBER 14, 2018

These offer applications with open APIs provide a new level of customization and integration. even small business is taking advantage of sophisticated analytics to turn data. Personalize the customer experience, make sense of big data to turn insights into actionable plans. Continued Emphasis – Self-Serve Documentation.

Call Center 21

Call Center Customer centricity Analytics APIs 21

AWS Machine Learning

JANUARY 26, 2024

Accelerate your security and AI/ML learning with best practices guidance, training, and certification AWS also curates recommendations from Best Practices for Security, Identity, & Compliance and AWS Security Documentation to help you identify ways to secure your training, development, testing, and operational environments.

Best practices 137

Best practices Government Engineering Accountability 137

Stratifyd

JANUARY 3, 2019

Maintain and develop Stratifyd’s API layer and/or analytics pipeline. Design, implement, and document new platform features and associated unit tests. Professional experience working with systems designed to deliver and operate on streaming data in near-real-time, or personal projects related to the same. and Python/C API.

Engineering 40

Engineering APIs Analytics Healthcare 40