Favorite With the number of cameras and sensors deployed growing exponentially, companies across industries are consuming more video than ever before. Additionally, advancements in analytics have expanded potential use cases, and these devices are now used to improve business operations and intelligence. In turn, the ability to effectively process video
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Shared by AWS Machine Learning August 28, 2021
Favorite We are excited to announce Aria, Amazon Polly’s first New Zealand English Neural text-to-speech (NTTS) voice. Similar to other Amazon Polly voices, Aria is developed as a voice that sounds bright, natural, and upbeat. This new voice for Aotearoa (New Zealand in Māori) is uniquely Kiwi. It includes a
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Shared by AWS Machine Learning August 28, 2021
Favorite The celebrity recognition feature in Amazon Rekognition automatically recognizes tens of thousands of well-known personalities in images and videos using machine learning (ML). Celebrity recognition significantly reduces the repetitive manual effort required to tag produced media content and make it readily searchable. Starting today, we’re updating our models to
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Shared by AWS Machine Learning August 27, 2021
Favorite With Amazon SageMaker Pipelines, you can create, automate, and manage end-to-end machine learning (ML) workflows at scale. SageMaker Projects build on SageMaker Pipelines by providing several MLOps templates that automate model building and deployment pipelines using continuous integration and continuous delivery (CI/CD). To help you get started, SageMaker Pipelines
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Shared by AWS Machine Learning August 26, 2021
Favorite Multiple pieces of information are often required to complete a task or to process a query. For example, when talking to an insurance agent, a caller might ask, “Can you provide me quotes for home, auto, and boat?” The agent recognizes this as a list of policy types before
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Shared by AWS Machine Learning August 25, 2021
Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning. It provides a single, web-based visual interface where you can perform all ML development steps required to build, train, and deploy models. You can quickly upload data, create new notebooks, train and tune models, move
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Shared by AWS Machine Learning August 25, 2021
Favorite “Farmers feed the entire world — so how might we support them to be resilient and build sustainable systems that also support global food security?” It’s a question that Diana Akrong found herself asking last year. Diana is a UX researcher based in Accra, Ghana, and the founding member
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Shared by Google AI Technology August 23, 2021
Favorite Here’s another post from the archives (corrected for some inaccuracy) which makes the case that much of the confusion around Knowledge Management may be due to an uncharacteristic deficiency in the English Language. Knowledge Management has always been in a state of confusion. There is no established understanding of
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Shared by Nick Milton August 23, 2021
Favorite Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. Although Studio provides all the tools you need to take your models from experimentation to production, you need a robust and secure model
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Shared by AWS Machine Learning August 19, 2021
Favorite In Part 1 of this series of posts, we offered step-by-step guidance for using Amazon SageMaker, SageMaker projects and Amazon SageMaker Pipelines, and AWS services such as Amazon Virtual Private Cloud (Amazon VPC), AWS CloudFormation, AWS Key Management Service (AWS KMS), and AWS Identity and Access Management (IAM) to
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Shared by AWS Machine Learning August 19, 2021
Shared by AWS Machine Learning August 28, 2021
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