APIs, Big data and Healthcare - Customer Contact Central

Intelligent healthcare forms analysis with Amazon Bedrock

AWS Machine Learning

AUGUST 13, 2024

Generative artificial intelligence (AI) provides an opportunity for improvements in healthcare by combining and analyzing structured and unstructured data across previously disconnected silos. Generative AI can help raise the bar on efficiency and effectiveness across the full scope of healthcare delivery.

Healthcare

Healthcare APIs Consulting Consulting

Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning

SEPTEMBER 3, 2024

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. However, managing the complex infrastructure required for big data workloads has traditionally been a significant challenge, often requiring specialized expertise.

Big data

Big data Engineering Accountability Real estate

Accelerate analysis and discovery of cancer biomarkers with Amazon Bedrock Agents

AWS Machine Learning

NOVEMBER 19, 2024

We showcase a variety of tools including database retrieval with Text2SQL, statistical models and visual charts with scientific libraries, biomedical literature search with public APIs and internal evidence, and medical image processing with Amazon SageMaker jobs. Architecture diagram showing Agents for Bedrock system flow.

APIs

APIs Healthcare Engineering Banking

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

FEBRUARY 29, 2024

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs

APIs Healthcare Scripts Enterprise

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

NOVEMBER 14, 2024

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. We will start by using the SageMaker Studio UI and then by using APIs.

Government

Government Management APIs Accountability

Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

NOVEMBER 3, 2022

Before you get started, refer to Part 1 for a high-level overview of the insurance use case with IDP and details about the data capture and classification stages. In Part 1, we saw how to use Amazon Textract APIs to extract information like forms and tables from documents, and how to analyze invoices and identity documents.

Analytics

Analytics APIs Healthcare Big data

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning

NOVEMBER 13, 2024

This transparency is particularly important for registered models, which are often deployed in high-stakes or regulated industries, such as financial services and healthcare. Integrate a model version in the model registry with model cards In this section, we provide API implementation details for testing this in your own environment.

Government

Government Engineering Metrics APIs

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

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

Scripts Engineering APIs Big data

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

AWS Machine Learning

MARCH 23, 2023

Leidos is a FORTUNE 500 science and technology solutions leader working to address some of the world’s toughest challenges in the defense, intelligence, homeland security, civil, and healthcare markets. Applications and services can call the deployed endpoint directly or through a deployed serverless Amazon API Gateway architecture.

Scripts

Scripts APIs Government Analytics

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

AUGUST 2, 2023

It has applications in areas where data is multi-modal such as ecommerce, where data contains text in the form of metadata as well as images, or in healthcare, where data could contain MRIs or CT scans along with doctor’s notes and diagnoses, to name a few use cases. However, we can use CDE for a wider range of use cases.

Enterprise

Enterprise Healthcare APIs Big data

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

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

Engineering Analytics APIs Enterprise

The IoT Chronicles Part 2: Three Big Security Threats—and How to Solve Them

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

APIs Transportation Enterprise Healthcare

Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

AWS Machine Learning

AUGUST 3, 2023

Finally, we show how you can integrate this car pose detection solution into your existing web application using services like Amazon API Gateway and AWS Amplify. For each option, we host an AWS Lambda function behind an API Gateway that is exposed to our mock application. Aamna Najmi is a Data Scientist with AWS Professional Services.

APIs

APIs Scripts Engineering Technical Support

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

SEPTEMBER 9, 2022

Prior to our adoption of Kubeflow on AWS, our data scientists used a standardized set of tools and a process that allowed flexibility in the technology and workflow used to train a given model. This means that user access can be controlled on the Kubeflow UI but not over the Kubernetes API via Kubectl.

Engineering

Engineering Healthcare APIs Scripts

Senior back-end software engineer

Stratifyd

JANUARY 3, 2019

Maintain and develop Stratifyd’s API layer and/or analytics pipeline. 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. Experience and/or knowledge of AI, Big Data, Tech. Stratifyd, Inc.

Engineering

Engineering APIs Analytics Healthcare

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

JANUARY 26, 2024

This is backed by our deep set of over 300 cloud security tools and the trust of our millions of customers, including the most security-sensitive organizations like government, healthcare, and financial services. Ram Vittal is a Principal ML Solutions Architect at AWS.

Best practices

Best practices Government Engineering Accountability

Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning

OCTOBER 23, 2024

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. The integration with Amazon Bedrock is achieved through the Amazon Bedrock InvokeModel APIs.

Enterprise

Enterprise APIs Engineering Government

Harness the power of AI and ML using Splunk and Amazon SageMaker Canvas

AWS Machine Learning

AUGUST 12, 2024

The Step Functions state machine is configured with an AWS Lambda function to retrieve data from the Splunk index using the Splunk Enterprise SDK for Python. The SPL query requested through this REST API call is scoped to only retrieve the data of interest. Create the dataset SageMaker Canvas supports Athena as a data source.

Engineering

Engineering APIs Healthcare Analytics

Customer Contact Central

Intelligent healthcare forms analysis with Amazon Bedrock

Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

Trending Sources

Accelerate analysis and discovery of cancer biomarkers with Amazon Bedrock Agents

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

The IoT Chronicles Part 2: Three Big Security Threats—and How to Solve Them

Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

Senior back-end software engineer

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

Harness the power of AI and ML using Splunk and Amazon SageMaker Canvas

Stay Connected

Intelligent healthcare forms analysis with Amazon Bedrock

Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

Trending Sources

Accelerate analysis and discovery of cancer biomarkers with Amazon Bedrock Agents

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

The IoT Chronicles Part 2: Three Big Security Threats—and How to Solve Them

Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

Senior back-end software engineer

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

Harness the power of AI and ML using Splunk and Amazon SageMaker Canvas

Stay Connected

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction