AWS Architecture Blog

Category: Artificial Intelligence

Figure 3. FL prototype deployed on Amazon ECS Fargate containers and AWS IoT Greengrass cores.

Applying Federated Learning for ML at the Edge

Federated Learning (FL) is an emerging approach to machine learning (ML) where model training data is not stored in a central location. During ML training, we typically need to access the entire training dataset on a single machine. For purposes of performance scaling, we divide the training data between multiple CPUs, multiple GPUs, or a […]

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Figure 2. Extending the solution

Scale Up Language Detection with Amazon Comprehend and S3 Batch Operations

Organizations have been collecting text data for years. Text data can help you intelligently address a range of challenges, from customer experience to analytics. These mixed language, unstructured datasets can contain a wealth of information within business documents, emails, and webpages. If you’re able to process and interpret it, this information can provide insight that […]

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Figure 1. Architecture for batch inference at scale with Amazon SageMaker

Batch Inference at Scale with Amazon SageMaker

Running machine learning (ML) inference on large datasets is a challenge faced by many companies. There are several approaches and architecture patterns to help you tackle this problem. But no single solution may deliver the desired results for efficiency and cost effectiveness. In this blog post, we will outline a few factors that can help […]

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Figure 1. Well-Architected Machine Learning Lifecycle

Introducing the new AWS Well-Architected Machine Learning Lens

The AWS Well-Architected Framework provides you with a formal approach to compare your workloads against best practices. It also includes guidance on how to make improvements. Machine learning (ML) algorithms discover and learn patterns in data, and construct mathematical models to predict future data. These solutions can revolutionize lives through better diagnoses of diseases, environmental […]

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Field Notes: Build a Cross-Validation Machine Learning Model Pipeline at Scale with Amazon SageMaker

When building a machine learning algorithm, such as a regression or classification algorithm, a common goal is to produce a generalized model. This is so that it performs well on new data that the model has not seen before. Overfitting and underfitting are two fundamental causes of poor performance for machine learning models. A model […]

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Top 5

Top 5: Featured Architecture Content for September

The AWS Architecture Center provides new and notable reference architecture diagrams, vetted architecture solutions, AWS Well-Architected best practices, whitepapers, and more. This blog post features some of our best picks from the new and newly updated content we released in the past month. 1. AWS Best Practices for DDoS Resiliency Prioritizing the availability and responsiveness […]

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Figure 8. Architecture diagram of entire data collection and classification process

Serverless Architecture for a Structured Data Mining Solution

Many businesses have an essential need for structured data stored in their own database for business operations and offerings. For example, a company that produces electronics may want to store a structured dataset of parts. This requires the following properties: color, weight, connector type, and more. This data may already be available from external sources. […]

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Field Notes: How to Prepare Large Text Files for Processing with Amazon Translate and Amazon Comprehend

Biopharmaceutical manufacturing is a highly regulated industry where deviation documents are used to optimize manufacturing processes. Deviation documents in biopharmaceutical manufacturing processes are geographically diverse, spanning multiple countries and languages. The document corpus is complex, with additional requirements for complete encryption. Therefore, to reduce downtime and increase process efficiency, it is critical to automate the […]

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Figure 7. Fan out design pattern including secondary pipeline for deleting images

Get Started with Amazon S3 Event Driven Design Patterns

Event driven programs use events to initiate succeeding steps in a process. For example, the completion of an upload job may then initiate an image processing job. This allows developers to create complex architectures by using the principle of decoupling. Decoupling is preferable for many workflows, as it allows each component to perform its tasks […]

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Figure 2: Automated batch ACT translation solution architecture

Speed Up Translation Jobs with a Fully Automated Translation System Assistant

Like other industries, translation and localization companies face the challenge of providing fast delivery at a low cost. To address this challenge, organizations use Machine Translation (MT) to complement their translator teams. MT is the use of automated software that translates text without the need of human involvement. One of the most recent advancements is […]

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