AWS Machine Learning

Amazon SageMaker enables organizations to build, train, and deploy machine learning models. Consumer-facing organizations can use it to enrich their customers’ experiences, for example, by making personalized p […]

Battlesnake is an AI competition based on the traditional snake game in which multiple AI-powered snakes compete to be the last snake surviving. Battlesnake attracts a community of developers at all levels. […]

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. In addition to building ML models […]

The AWS DeepRacer League is the world’s first autonomous racing league and is open to anyone. In 2019, tens of thousands of developers from around the world took part in a race against the clock to see who had t […]

Virtual screening is a computational methodology used in drug or materials discovery by searching a vast amount of molecules libraries to identify the structures that are most likely to show the target […]

Amazon CodeGuru (Preview) is a service launched at AWS re:Invent 2019 that analyzes the performance characteristics of your application and provides automatic recommendations on ways to improve. It does this by […]

Amazon Forecast is a fully managed service that uses machine learning (ML) to generate highly accurate forecasts without requiring any prior ML experience. Forecast is applicable in a wide variety of use cases, […]

The AWS Machine Learning Research Awards (MLRA) provides unrestricted cash funds and AWS Promotional Credits to academics to advance the frontiers of machine learning (ML) and its applications. MLRA is pleased to […]

AWS introduced the Machine Learning (ML) Solutions Lab a little over two years ago to connect our machine learning experts and data scientists with AWS customers.  Our goal was to help our customers solve their […]

Amazon SageMaker Operators for Kubernetes allows you to augment your existing Kubernetes cluster with SageMaker hosted endpoints.
Machine learning inferencing requires investment to create a reliable and […]

As machine learning (ML) becomes a larger part of companies’ core business, there is a greater emphasis on reducing the time from model creation to deployment. In November of 2019, AWS released the AWS Step F […]

You have many choices for building, training, and deploying machine learning (ML) models. Weighing the financial considerations of different cloud solutions requires detailed analysis. You must consider the […]

The National Health Care Anti-Fraud Association (NHCAA) estimates that healthcare fraud costs the nation approximately $68 billion annually—3% of the nation’s $2.26 trillion in healthcare spending. This is a con […]

Amazon Personalize is a machine learning service which enables you to personalize your website, app, ads, emails, and more, with custom machine learning models which can be created in Amazon Personalize, with no […]

Enterprises often rely on unique identifiers to look up information on accounts or events. For example, airlines use confirmation codes to locate itineraries, and insurance companies use policy IDs to retrieve […]

AWS is pleased to announce a new feature in Amazon Polly called Brand Voice, a capability in which you can work with the Amazon Polly team of AI research scientists and linguists to build an exclusive, […]

Amazon re:MARS 2020 is June 16–19 in Las Vegas, Nevada. Arrive early for our new Developer Day, then join Jeff Bezos, Jon Favreau, and others at Amazon’s event dedicated to machine learning, automation, rob […]

This is a guest post from Millennium Management. In their own words, “Millennium Management is a global investment management firm, established in 1989, with over 2,900 employees and $39.2 billion in assets u […]

A critical success factor in machine learning (ML) is the cleanliness and accuracy of training datesets. Training with mislabeled or inaccurate data can lead to a poorly performing model. But how can you easily […]

Amazon Comprehend is a fully managed natural language processing (NLP) service that enables text analytics to extract insights from the content of documents. Amazon Comprehend supports custom classification and […]