AWS Machine Learning Blog

Category: Amazon Machine Learning

Solution Architecture Diagram

Personalize your machine translation results by using fuzzy matching with Amazon Translate

A person’s vernacular is part of the characteristics that make them unique. There are often countless different ways to express one specific idea. When a firm communicates with their customers, it’s critical that the message is delivered in a way that best represents the information they’re trying to convey. This becomes even more important when […]

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Whitepaper: Machine Learning Best Practices in Healthcare and Life Sciences

For customers looking to implement a GxP-compliant environment on AWS for artificial intelligence (AI) and machine learning (ML) systems, we have released a new whitepaper: Machine Learning Best Practices in Healthcare and Life Sciences. This whitepaper provides an overview of security and good ML compliance practices and guidance on building GxP-regulated AI/ML systems using AWS […]

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Secure Amazon S3 access for isolated Amazon SageMaker notebook instances

In this post, we will demonstrate how to securely launch notebook instances in a private subnet of an Amazon Virtual Private Cloud (Amazon VPC), with internet access disabled, and to securely connect to Amazon Simple Storage Service (Amazon S3) using VPC endpoints. This post is for network and security architects that support decentralized data science […]

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Enhance your SaaS offering with a data science workbench powered by Amazon SageMaker Studio

Many software as a service (SaaS) providers across various industries are adding machine learning (ML) and artificial intelligence (AI) capabilities to their SaaS offerings to address use cases like personalized product recommendation, fraud detection, and accurate demand protection. Some SaaS providers want to build such ML and AI capabilities themselves and deploy them in a […]

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Announcing the AWS DeepRacer League 2022

Unleash the power of machine learning (ML) through hands-on learning and compete for prizes and glory. The AWS DeepRacer League is the world’s first global autonomous racing competition driven by reinforcement learning; bringing together students, professionals, and enthusiasts from almost every continent. I’m Tomasz Ptak, a senior software engineer at Duco, an AWS Machine Learning […]

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Normalize datasets used to train machine learning model

Reduce costs and complexity of ML preprocessing with Amazon S3 Object Lambda

Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. Often, customers have objects in S3 buckets that need further processing to be used effectively by consuming applications. Data engineers must support these application-specific data views with trade-offs between persisting derived copies or transforming data […]

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Implement MLOps using AWS pre-trained AI Services with AWS Organizations

The AWS Machine Learning Operations (MLOps) framework is an iterative and repetitive process for evolving AI models over time. Like DevOps, practitioners gain efficiencies promoting their artifacts through various environments (such as quality assurance, integration, and production) for quality control. In parallel, customers rapidly adopt multi-account strategies through AWS Organizations and AWS Control Tower to […]

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Distributed fine-tuning of a BERT Large model for a Question-Answering Task using Hugging Face Transformers on Amazon SageMaker

From training new models to deploying them in production, Amazon SageMaker offers the most complete set of tools for startups and enterprises to harness the power of machine learning (ML) and Deep Learning. With its Transformers open-source library and ML platform, Hugging Face makes transfer learning and the latest ML models accessible to the global […]

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Computer vision-based anomaly detection using Amazon Lookout for Vision and AWS Panorama

This is the second post in the two-part series on how Tyson Foods Inc., is using computer vision applications at the edge to automate industrial processes inside their meat processing plants. In Part 1, we discussed an inventory counting application at packaging lines built with Amazon SageMaker and AWS Panorama . In this post, we […]

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Graph-based recommendation system with Neptune ML: An illustration on social network link prediction challenges

Recommendation systems are one of the most widely adopted machine learning (ML) technologies in real-world applications, ranging from social networks to ecommerce platforms. Users of many online systems rely on recommendation systems to make new friendships, discover new music according to suggested music lists, or even make ecommerce purchase decisions based on the recommended products. […]

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