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

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. Vinnie Saini is a Senior Solutions Architect at Amazon Web Services (AWS) based in Toronto, Canada.

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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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Database SQL AWS AI 101

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 AI AI Database 138

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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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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Dataconomy

FEBRUARY 6, 2024

Artificial intelligence and machine learning are no longer the elements of science fiction; they’re the realities of today. According to Precedence Research , the global market size of machine learning will grow at a CAGR of a staggering 35% and reach around $771.38 billion by 2032. billion by 2032.

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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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Heartbeat

DECEMBER 27, 2023

Photo by Ian Taylor on Unsplash This article will comprehensively create, deploy, and execute machine learning application containers using the Docker tool. It will further explain the various containerization terms and the importance of this technology to the machine learning workflow. What is Docker?

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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. Choose Create experiment.

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Pickl AI

FEBRUARY 23, 2025

Apache Spark Apache Spark is a unified analytics engine for Big Data processing, with built-in modules for streaming, SQL, Machine Learning , and graph processing. Use Cases : Netflix utilizes Spark for real-time analytics and Machine Learning algorithms to enhance user experience through personalized recommendations.

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