AWS Machine Learning Blog

FEBRUARY 5, 2025

Click here to open the AWS console and follow along. Developed by Todd Gamblin at the Lawrence Livermore National Laboratory in 2013, Spack addresses the limitations of traditional package managers in high-performance computing (HPC) environments. About the Authors Nick Biso is a Machine Learning Engineer at AWS Professional Services.

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AWS Machine Learning Blog

MAY 24, 2023

In this three-part series, we present a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. In the following sections, we discuss the stages of the process in detail.

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AWS Machine Learning Blog

FEBRUARY 1, 2024

Consider the following picture, which is an AWS view of the a16z emerging application stack for large language models (LLMs). This includes native AWS services like Amazon OpenSearch Service and Amazon Aurora. Is your vector database highly available in a single AWS Region? Vector database features built into other services.

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AWS Machine Learning Blog

JUNE 13, 2023

Overall, implementing a modern data architecture and generative AI techniques with AWS is a promising approach for gleaning and disseminating key insights from diverse, expansive data at an enterprise scale. AWS also offers foundation models through Amazon SageMaker JumpStart as Amazon SageMaker endpoints.

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AWS Machine Learning Blog

FEBRUARY 26, 2025

Pattern was founded in 2013 and has expanded to over 1,700 team members in 22 global locations, addressing the growing need for specialized ecommerce expertise. In this post, we share how Pattern uses AWS services to process trillions of data points to deliver actionable insights, optimizing product listings across multiple services.

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AWS Machine Learning Blog

FEBRUARY 2, 2024

The embeddings are captured in Amazon Simple Storage Service (Amazon S3) via Amazon Kinesis Data Firehose , and we run a combination of AWS Glue extract, transform, and load (ETL) jobs and Jupyter notebooks to perform the embedding analysis. For more information about AWS CDK installation, refer to Getting started with the AWS CDK.

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AWS Machine Learning Blog

JUNE 23, 2023

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code.

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AWS Machine Learning Blog

JANUARY 4, 2024

In this pattern, we use Retrieval Augmented Generation using vector embeddings stores, like Amazon Titan Embeddings or Cohere Embed , on Amazon Bedrock from a central data catalog, like AWS Glue Data Catalog , of databases within an organization. In entered the Big Data space in 2013 and continues to explore that area.

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Flipboard

JULY 19, 2023

As part of the post-processing, an AWS Lambda function inserts special markers into the text indicating page boundaries. Another Lambda function picks up that message and starts an Amazon Elastic Container Service (Amazon ECS) AWS Fargate task. About the author Randy DeFauw is a Senior Principal Solutions Architect at AWS.

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Heartbeat

DECEMBER 27, 2023

However, the emergence of the open-source Docker engine by Solomon Hykes in 2013 accelerated the adoption of the technology. The machine learning (ML) lifecycle defines steps to derive values to meet business objectives using ML and artificial intelligence (AI). What is Docker? Docker is the most popular container technology.

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Flipboard

NOVEMBER 24, 2023

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

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Pickl AI

FEBRUARY 23, 2025

Amazon EMR (Elastic MapReduce) Amazon EMR is a cloud-native Big Data platform that simplifies running Big Data frameworks such as Apache Hadoop and Apache Spark on AWS. Statistics : According to AWS reports, EMR reduces the time required for Big Data processing tasks by up to 90% compared to traditional methods.

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