AWS Machine Learning Blog

Customer service conversations typically revolve around one or more topics and contain related questions. Answering these questions seamlessly is essential for a good conversational experience. For example, as part of a car rental reservation, you have queries such as, “What’s the charge for an additional driver?” or, “Do you have car seats for kids?” Starting […]

In today’s world, social media has become a place where customers share their experiences with services that they consume. Every telecom provider wants to have the ability to understand their customer pain points as soon as possible and to do this carriers frequently establish a social media team within their NOC (network operation center). This […]

Amazon Polly turns text into lifelike speech, allowing you to create voice-enabled applications. We’re excited to announce the general availability of a new US English child voice—Kevin. Kevin’s voice was developed using the latest Neural Text-to-Speech (NTTS) technology, making it sound natural and human-like. This voice imitates the voice of a male child. Have a […]

AWS DeepRacer is a fun and easy way for developers with no prior experience to get started with machine learning (ML). At the end of the 2019 season, the AWS DeepRacer League engaged the Amazon ML Solutions Lab to develop a new sports analytics feature for the AWS DeepRacer Championship Cup at re:Invent 2019. The […]

Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to quickly build, train, and deploy machine learning (ML) models. Tens of thousands of customers, including Intuit, Voodoo, ADP, Cerner, Dow Jones, and Thomson Reuters, use Amazon SageMaker to remove the heavy lifting from the ML process. With Amazon SageMaker, […]

Industries like healthcare, media, and social media platforms use image analysis workflows to identify objects and entities within pictures to understand the whole image. For example, an ecommerce website might use objects present in an image to surface relevant search results. Sometimes image analysis may be difficult when images are blurry or more nuanced. In […]

Amazon SageMaker Ground Truth now supports labeling 3D point cloud data. For more information about the launched feature set, see this AWS News Blog post. In this blog post, we specifically cover how to perform the required data transformations of your 3D point cloud data to create a labeling job in SageMaker Ground Truth for […]

Amazon Rekognition is a machine learning (ML) based image and vision analysis service that can identify objects, people, text, scenes, and activities in images and videos, and detect any inappropriate content. Amazon Rekognition text detection enables you to recognize and extract textual content from images and videos. For example, in image sharing and social media […]

This blog post was last reviewed or updated April, 2022 with updates to how filters are configured. Today, we are pleased to announce the addition of Recommendation Filters in Amazon Personalize, which improve the relevance of personalized recommendations by filtering out recommendations for products that users have already purchased, videos they have already watched, or […]

Amazon SageMaker is a fully managed service that allows you to build, train, and deploy machine learning (ML) models quickly. Amazon SageMaker removes the heavy lifting from each step of the ML process to make it easier to develop high-quality models. In August 2019, Amazon SageMaker announced the availability of the pre-installed R kernel in […]