AWS Machine Learning Blog

Category: Intermediate (200)

Create your RStudio on Amazon SageMaker licensed or trial environment in three easy steps

RStudio on Amazon SageMaker is the first fully managed cloud-based Posit Workbench (formerly known as RStudio Workbench). RStudio on Amazon SageMaker removes the need for you to manage the underlying Posit Workbench infrastructure, so your teams can concentrate on producing value for your business. You can quickly launch the familiar RStudio integrated development environment (IDE) […]

Promote search content using Featured Results for Amazon Kendra

Amazon Kendra is an intelligent search service powered by machine learning (ML). We are excited to announce the launch of Amazon Kendra Featured Results. This new feature makes specific documents or content appear at the top of the search results page whenever a user issues a certain query. You can use Featured Results to improve […]

Automatic image cropping with Amazon Rekognition

Digital publishers are continuously looking for ways to streamline and automate their media workflows in order to generate and publish new content as rapidly as they can. Many publishers have a large library of stock images that they use for their articles. These images can be reused many times for different stories, especially when the […]

Automate and implement version control for Amazon Kendra FAQs

Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. Amazon Kendra FAQs allow users to upload […]

Bundesliga Match Fact Ball Recovery Time: Quantifying teams’ success in pressing opponents on AWS

In football, ball possession is a strong predictor for team success. It’s hard to control the game without having control over the ball. In the past three Bundesliga seasons, as well as in the current season (at the time of this writing), Bayern Munich is ranked first in the table and in ball possession percentage, […]

Bundesliga Match Fact Keeper Efficiency: Comparing keepers’ performances objectively using machine learning on AWS

The Bundesliga is renowned for its exceptional goalkeepers, making it potentially the most prominent among Europe’s top five leagues in this regard. Apart from the widely recognized Manuel Neuer, the Bundesliga has produced remarkable goalkeepers who have excelled in other leagues, including the likes of Marc-André ter Stegen, who is a superstar at Barcelona. In […]

Achieve effective business outcomes with no-code machine learning using Amazon SageMaker Canvas

On November 30, 2021, we announced the general availability of Amazon SageMaker Canvas, a visual point-and-click interface that enables business analysts to generate highly accurate machine learning (ML) predictions without having to write a single line of code. With Canvas, you can take ML mainstream throughout your organization so business analysts without data science or […]

Enable predictive maintenance for line of business users with Amazon Lookout for Equipment

Predictive maintenance is a data-driven maintenance strategy for monitoring industrial assets in order to detect anomalies in equipment operations and health that could lead to equipment failures. Through proactive monitoring of an asset’s condition, maintenance personnel can be alerted before issues occur, thereby avoiding costly unplanned downtime, which in turn leads to an increase in […]

Automate Amazon Rekognition Custom Labels model training and deployment using AWS Step Functions

With Amazon Rekognition Custom Labels, you can have Amazon Rekognition train a custom model for object detection or image classification specific to your business needs. For example, Rekognition Custom Labels can find your logo in social media posts, identify your products on store shelves, classify machine parts in an assembly line, distinguish healthy and infected […]

Bring legacy machine learning code into Amazon SageMaker using AWS Step Functions

Tens of thousands of AWS customers use AWS machine learning (ML) services to accelerate their ML development with fully managed infrastructure and tools. For customers who have been developing ML models on premises, such as their local desktop, they want to migrate their legacy ML models to the AWS Cloud to fully take advantage of […]