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AWS Architecture Blog

Category: Amazon Machine Learning

Training a call center fraud detection model for IVR calls with Amazon SageMaker Canvas

This blog post will show you how to use the power of ML to build a fraud-detection model using Amazon SageMaker Canvas, a no-code/low-code ML service that business analysts and domain experts can use to build, train, and deploy ML models without requiring extensive ML expertise.

Use generative AI on AWS for efficient clinical document analysis

In this post, we show how Clario uses the AWS platform to accelerate clinical document analysis.

Transform lease agreement workflows with Amazon Bedrock

This post explores how Amazon Bedrock can transform property management operations and optimize costs. We examine a practical approach to tackle challenges such as processing high volumes of lease agreements, maintaining compliance with varied regulatory requirements.

Let’s Architect! Modern data architectures

Data is the fuel for AI; modern data is even more important for generative AI and advanced data analytics, producing more accurate, relevant, and impactful results. Modern data comes in various forms: real-time, unstructured, or user-generated. Each form requires a different solution. AWS’s data journey began with Amazon Simple Storage Service (Amazon S3) in 2006, […]

Diagram showing the Amazon Bedrock solution to simplify and automate billing

Simplify and automate bill processing with Amazon Bedrock

This post was co-written with Shyam Narayan, a leader in the Accenture AWS Business Group, and Hui Yee Leong, a DevOps and platform engineer, both based in Australia. Hui and Shyam specialize in designing and implementing complex AWS transformation programs across a wide range of industries. Enterprises that operate out of multiple locations such as […]

Genomics workflows, Part 7: analyze public RNA sequencing data using AWS HealthOmics

Genomics workflows process petabyte-scale datasets on large pools of compute resources. In this blog post, we discuss how life science organizations can use Amazon Web Services (AWS) to run transcriptomic sequencing data analysis using public datasets. This allows users to quickly test research hypotheses against larger datasets in support of clinical diagnostics. We use AWS […]

Let’s Architect! Learn About Machine Learning on AWS

A data-driven approach empowers businesses to make informed decisions based on accurate predictions and forecasts, leading to improved operational efficiency and resource optimization. Machine learning (ML) systems have the remarkable ability to continuously learn and adapt, improving their performance over time as they are exposed to more data. This self-learning capability ensures that organizations can […]

Let’s Architect! Discovering Generative AI on AWS

Generative artificial intelligence (generative AI) is a type of AI used to generate content, including conversations, images, videos, and music. Generative AI can be used directly to build customer-facing features (a chatbot or an image generator), or it can serve as an underlying component in a more complex system. For example, it can generate embeddings […]