Category: Amazon Machine Learning

Amazon SageMaker is a fully managed service that provides every machine learning (ML) developer and data scientist the ability to build, train, and deploy ML models at scale. Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for ML. Amazon SageMaker Studio provides all the tools you need to take your models from experimentation […]

Feature engineering is expensive and time-consuming, which may lead you to adopt a feature store for managing features across teams and models. Unfortunately, machine learning (ML) lineage solutions have yet to adapt to this new concept of feature management. To achieve the full benefits of a feature store by enabling feature reuse, you need to […]

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 […]

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 […]

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 […]

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 […]

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 […]

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, […]

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 […]

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, you may have […]