AWS Machine Learning Blog

Category: Amazon Machine Learning

Detect industrial defects at low latency with computer vision at the edge with Amazon SageMaker Edge

Defect detection in manufacturing can benefit from machine learning (ML) and computer vision (CV) to reduce operational costs, improve time to market, and increase productivity, quality, and safety. According to McKinsey, the “benefits of defect detection and other Industry 4.0 applications are estimated to create a potential value of $3.7 trillion in 2025 for manufacturers […]

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Create a dashboard with SEC text for financial NLP in Amazon SageMaker JumpStart

Amazon SageMaker JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few clicks. JumpStart also includes a collection of multimodal financial text analysis tools, including example notebooks, text models, and […]

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Accelerate computer vision training using GPU preprocessing with NVIDIA DALI on Amazon SageMaker

AWS customers are increasingly training and fine-tuning large computer vision (CV) models with hundreds of terabytes of data and millions of parameters. For example, advanced driver assistance systems (ADAS) train perception models to detect pedestrians, road signs, vehicles, traffic lights, and other objects. Identity verification systems for the financial services industry train CV models to […]

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Choose the best AI accelerator and model compilation for computer vision inference with Amazon SageMaker

AWS customers are increasingly building applications that are enhanced with predictions from computer vision models. For example, a fitness application monitors the body posture of users while exercising in front of a camera and provides live feedback to the users as well as periodic insights. Similarly, an inventory inspection tool in a large warehouse captures […]

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Amazon SageMaker rated as top AI Service Cloud in analyst firm KuppingerCole’s evaluation of AI Service Clouds

As more European organizations move from experimentation to production for AI projects, the importance of running these projects on a scalable, secure, and cost-efficient platform becomes clear. Building AI solutions from scratch is often beyond the capabilities of many organizations, especially because it requires in-house AI expertise, which is in short supply. According to analyst […]

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Gamify Amazon SageMaker Ground Truth labeling workflows via a bar chart race

Labeling is an indispensable stage of data preprocessing in supervised learning. Amazon SageMaker Ground Truth is a fully managed data labeling service that makes it easy to build highly accurate training datasets for machine learning. Ground Truth helps improve the quality of labels through annotation consolidation and audit workflows. Ground Truth is easy to use, […]

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Organize product data to your taxonomy with Amazon SageMaker

When companies deal with data that comes from various sources or the collection of this data has changed over time, the data often becomes difficult to organize. Perhaps you have product category names that are similar but don’t match, and on your website you want to surface these products as a group. Therefore, you need […]

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Train and deploy deep learning models using JAX with Amazon SageMaker

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. Typically, you can use the pre-built and optimized training and inference containers that have been optimized for AWS hardware. Although those containers cover many deep learning workloads, […]

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Build, tune, and deploy an end-to-end churn prediction model using Amazon SageMaker Pipelines

The ability to predict that a particular customer is at a high risk of churning, while there is still time to do something about it, represents a huge potential revenue source for every online business. Depending on the industry and business objective, the problem statement can be multi-layered. The following are some business objectives based […]

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Bring structure to diverse documents with Amazon Textract and transformer-based models on Amazon SageMaker

From application forms, to identity documents, recent utility bills, and bank statements, many business processes today still rely on exchanging and analyzing human-readable documents—particularly in industries like financial services and law. In this post, we show how you can use Amazon SageMaker, an end-to-end platform for machine learning (ML), to automate especially challenging document analysis […]

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