APIs, Big data, Scripts and Technology - Customer Contact Central

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Fine-tune and deploy a summarizer model using the Hugging Face Amazon SageMaker containers bringing your own script

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

Scripts APIs Big data Engineering

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

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Webinars

How to Optimize Call Monitoring: Automate QA and Elevate Customer Experience

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Trending Sources

Build a custom UI for Amazon Q Business

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. You can also find the script on the GitHub repo.

APIs

APIs Enterprise Accountability Feedback

Webinars

How to Optimize Call Monitoring: Automate QA and Elevate Customer Experience

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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

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

AWS Machine Learning

JULY 25, 2022

Trumid is a financial technology company building tomorrow’s credit trading network—a marketplace for efficient trading, information dissemination, and execution between corporate bond market participants. The bond trading market has traditionally involved offline buyer/seller matching processes aided by rules-based technology.

Scripts

Scripts Engineering Analytics APIs

Reduce cost and development time with Amazon SageMaker Pipelines local mode

AWS Machine Learning

OCTOBER 4, 2022

Developers usually test their processing and training scripts locally, but the pipelines themselves are typically tested in the cloud. One of the main drivers for new innovations and applications in ML is the availability and amount of data along with cheaper compute options. Build your pipeline.

Scripts

Scripts Engineering Management APIs

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. iterdir(): if p_file.suffix == ".pth":

APIs

APIs Scripts Engineering Technical Support

How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

SEPTEMBER 9, 2022

When the message is received by the SQS queue, it triggers the AWS Lambda function to make an API call to the Amp catalog service. The Lambda function retrieves the desired show metadata, filters the metadata, and then sends the output metadata to Amazon Kinesis Data Streams. Data Engineer for Amp on Amazon. About the authors.

Analytics

Analytics Engineering APIs Metrics

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

AWS Machine Learning

APRIL 11, 2023

In the post Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication , we demonstrated how to build a private API to generate Amazon SageMaker Studio presigned URLs that are only accessible by an authenticated end-user within the corporate network from a single account.

APIs

APIs Accountability Scripts Enterprise

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. Each project maintained detailed documentation that outlined how each script was used to build the final model.

Engineering

Engineering Healthcare APIs Scripts

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

AWS Machine Learning

JANUARY 26, 2024

As your organization advances its use of emerging technologies such as generative AI and LLMs, overall organizational resiliency should be considered as a cornerstone of a layered defensive strategy to protect assets and lines of business from unintended consequences.

Best practices

Best practices Government Engineering Accountability

Securing MLflow in AWS: Fine-grained access control with AWS native services

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

APIs Government Accountability Scripts

Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

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. An AWS account with permissions to create AWS Identity and Access Management (IAM) policies and roles.

APIs

APIs Engineering Analytics Scripts

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

AWS Machine Learning

AUGUST 29, 2023

When a new version of the model is registered in the model registry, it triggers a notification to the responsible data scientist via Amazon SNS. When the review process is complete, the data scientist can proceed and approve the new version of the model in the model registry.

Scripts

Scripts APIs Enterprise Accountability

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning

DECEMBER 18, 2023

The SageMaker Canvas UI lets you seamlessly integrate data sources from the cloud or on-premises, merge datasets effortlessly, train precise models, and make predictions with emerging data—all without coding. Solution overview Users persist their transactional time series data in MongoDB Atlas.

Finance

Finance APIs Analytics Scripts

Fine-tune and deploy a summarizer model using the Hugging Face Amazon SageMaker containers bringing your own script

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

Webinars

Trending Sources

Build a custom UI for Amazon Q Business

Webinars

­­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

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

Reduce cost and development time with Amazon SageMaker Pipelines local mode

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

How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

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

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

Securing MLflow in AWS: Fine-grained access control with AWS native services

Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

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