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Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 2: Data preparation and model building with Amazon SageMaker Canvas

Favorite Part 1 covered the Snowflake database setup and established the foundational infrastructure for this no-code machine learning (ML) workflow. Part 2 of this blog series covers complete data preparation and model building workflow using Amazon SageMaker Canvas, demonstrating how to connect directly to Snowflake data sources, transform and prepare

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Shared by AWS Machine Learning August 21, 2026

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake environment

Favorite Healthcare, retail, and life sciences organizations generate massive quantities of operational data in cloud data warehouses like Snowflake. While these systems store and scale information efficiently, transforming that data into meaningful predictions remains a challenge. Traditional machine learning (ML) approaches require specialized teams, long development cycles, and heavy engineering

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Shared by AWS Machine Learning August 21, 2026

How Axonius built secure multi-tenant AI agents on Bedrock AgentCore

Favorite Independent Software Vendors (ISVs) are expanding their offerings and adding AI agents. Common considerations for organizations when adding agentic workloads include security, scalability, time to market, and cost tracking. ISVs have another dimension, they provide services to other organizations and need to manage agentic workloads for each customer. As

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Shared by AWS Machine Learning August 19, 2026

Improve contract search accuracy with auto-generated filters in Amazon Bedrock

Favorite Enterprises rely on large volumes of complex legal agreements to make critical business decisions — determining rights, renewal options, geographic restrictions, and compliance obligations. In industries like entertainment and media, where organizations manage thousands of contracts across multiple jurisdictions, this work remains largely manual: time-consuming, costly, and difficult to

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Shared by AWS Machine Learning August 19, 2026

How Jumio built a real-time feature store on AWS

Favorite If you’re managing a real-time feature store, you might be facing challenges such as data duplication, feature engineering, feature consistency, manual deployment, and latency. Jumio is an identity verification provider that helps businesses detect fraud and build digital trust. To provide these services in real time, Jumio’s machine learning

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Shared by AWS Machine Learning August 19, 2026

Implement vector-prompt document classification using Amazon Bedrock

Favorite Vector-prompt classification on Amazon Bedrock helps insurance companies accurately classify thousands of daily documents: policies, affidavits, endorsements, and regulatory forms, for compliance, claims, and customer service. Manual classification is time-consuming and error-prone, while traditional automated approaches struggle with documents that look similar but serve different purposes. A policy endorsement

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Shared by AWS Machine Learning August 19, 2026

Customize Amazon Quick embedded chat into your application

Favorite Amazon Quick embedded chat provides a conversational AI interface that you can integrate directly into your web application. Your users can ask questions, explore data, and get insights without leaving your application. However, a generic chat interface creates a disjointed experience. The chat interface must look and feel like

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Shared by AWS Machine Learning August 19, 2026