AWS Machine Learning Blog

Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning. It can reduce your labeling costs by up to 70% using automatic labeling. This blog post explains the Amazon SageMaker Ground Truth chaining feature with a few examples and its potential in labeling your datasets. Chaining reduces time and cost significantly […]

This is a guest post from Graham Pengelly, CTO, and James Jameson, the Commercial Lead, at CaptionHub. CaptionHub is a London-based company that focuses on video captioning and subtitling production for enterprise organizations. While the act of captioning—that is, taking video files and making sure the text on the screen reflects what’s being said accurately […]

If you’re like most companies, you wish to better understand your customers and your brand image. You’d like to track the success of your marketing campaigns, and the topics of interest—or frustration—for your customers. Social media promises to be a rich source of this kind of information, and many companies are beginning to collect, aggregate, […]

Machine learning (ML) lets enterprises unlock the true potential of their data, automate decisions, and transform their business processes to deliver exponential value to their customers. To help you take advantage of ML, Amazon SageMaker provides the ability to build, train, and deploy ML models quickly. Until recently, if you used Amazon SageMaker, you could […]

AWS DeepRacer, launched at re:Invent 2018, helps developers get hands on with reinforcement learning (RL).  Since then, thousands of people have developed and raced their models at 21 AWS DeepRacer League events at AWS Summits across the world, and virtually via the AWS DeepRacer console. Beyond the summits there have been several events at AWS […]

Machine learning (ML) is routinely used by countless businesses to assist with decision making. In most cases, however, the predictions and business decisions made by ML systems still require the intuition of human users to make judgment calls. In this post, I show how to combine ML with sensitivity analysis to develop a data-driven business […]

The AWS DeepRacer League is the world’s first autonomous racing league, open to anyone. Announced at re:Invent 2018, it puts machine learning in the hands of every developer in a fun and exciting way. Since March 2019, thousands of developers of all skill levels have competed for the chance to advance to the Championship Cup […]

When it comes to running distributed machine learning (ML) workloads, AWS offers you both managed and self-service offerings. Amazon SageMaker is a managed service that can help engineering, data science, and research teams save time and reduce operational overhead. AWS ParallelCluster is an open-source, self-service cluster management tool for customers who wish to maintain more […]

Accenture has a rich history of helping customers all over the world build artificial intelligence (AI) and machine learning (ML) powered solutions with AWS services. In doing so, they always look for new and engaging ways to develop their teams with the appropriate level of enablement and hands-on training. Accenture’s next ML initiative is rolling […]

Academic research and open-source software development are at the forefront of machine learning (ML) technology development. Since 2017, the AWS Machine Learning Research Awards (MLRA) has been aiming to advance machine learning by funding innovative research, training students, and providing researchers with access to the latest technology. MLRA has supported over 100 cutting-edge ML projects, […]