AWS Machine Learning Blog

Tag: AWS Customer

Real estate brokerage firm John L. Scott uses Amazon Textract and Amazon Comprehend to strike racially restrictive language from property deeds for homeowners

Founded more than 91 years ago in Seattle, John L. Scott Real Estate’s core value is Living Life as a Contribution®. The firm helps homebuyers find and buy the home of their dreams, while also helping sellers move into the next chapter of their home ownership journey. John L. Scott currently operates over 100 offices […]

Enhance sports narratives with natural language generation using Amazon SageMaker

This blog post was co-authored by Arbi Tamrazian, Director of Data Science and Machine Learning at Fox Sports. FOX Sports is the sports television arm of FOX Network. The company used machine learning (ML) and Amazon SageMaker to streamline the production of relevant in-game storylines for commentators to use during live broadcasts. “We collaborated with […]

Accelerating MLOps at Bayer Crop Science with Kubeflow Pipelines and Amazon SageMaker

This is a guest post by the data science team at Bayer Crop Science.  Farmers have always collected and evaluated a large amount of data with each growing season: seeds planted, crop protection inputs applied, crops harvested, and much more. The rise of data science and digital technologies provides farmers with a wealth of new […]

How Foxconn built an end-to-end forecasting solution in two months with Amazon Forecast

This is a guest post by Foxconn. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post.  In their own words, “Established in Taiwan in 1974, Hon Hai Technology Group (Foxconn) is the world’s largest electronics manufacturer. Foxconn is […]

Focusing on disaster response with Amazon Augmented AI and Mechanical Turk

It’s easy to distinguish a lake from a flood. But when you’re looking at an aerial photograph, factors like angle, altitude, cloud cover, and context can make the task more difficult. And when you need to identify 100,000 aerial images in order to give first responders the information they need to accelerate disaster response efforts? […]

Predicting soccer goals in near real time using computer vision

In a soccer game, fans get excited seeing a player sprint down the sideline during a counterattack or when a team is controlling the ball in the 18-yard box because those actions could lead to goals. However, it is difficult for human eyes to fully capture such fast movements, let alone predict goals. With machine […]

How Thomson Reuters accelerated research and development of natural language processing solutions with Amazon SageMaker

This post is co-written by John Duprey and Filippo Pompili from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted providers of answers, helping professionals make confident decisions and run better businesses. Teams of experts from TR bring together information, innovation, and confident insights to unravel complex situations, and their worldwide network […]

Customization, automation and scalability in customer service: Integrating Genesys Cloud and AWS Contact Center Intelligence

This is a guest post authored by Rebecca Owens and Julian Hernandez, who work at Genesys Cloud.  Legacy technology limits organizations in their ability to offer excellent customer service to users. Organizations must design, establish, and implement their customer relationship strategies while balancing against operational efficiency concerns. Another factor to consider is the constant evolution […]

How Xpertal is creating the Contact Center of the future with Amazon Lex

This is a joint blog post with AWS Solutions Architects, Jorge Alfaro Hidalgo and Mauricio Zajbert, and Chester Perez, the Contact Center Manager at Xpertal. Fomento Económico Mexicano, S.A.B. de C.V. (FEMSA) is a Mexican multinational beverage and retail company headquartered in Monterrey, Mexico. Fomento Económico Mexicano, S.A.B. de C.V., or FEMSA, is a Mexican […]

How DeepMap optimizes their video inference workflow with Amazon SageMaker Processing

Although we might think the world is already sufficiently mapped by the advent of global satellite images and street views, it’s far from complete because much of the world is still uncharted territory. Maps are designed for humans, and can’t be consumed by autonomous vehicles, which need a very different technology of maps with much […]