Favorite Amazon SageMaker Feature Store is a new capability of Amazon SageMaker that helps data scientists and machine learning (ML) engineers securely store, discover, and share curated data used in training and prediction workflows. As organizations build data-driven applications using ML, they’re constantly assembling and moving features between more and

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Shared by AWS Machine Learning March 24, 2021

Favorite You can now enable notifications for workflow status changes while using Amazon Forecast, allowing you to work seamlessly without the disruption of having to check if a particular workflow has completed. Additionally, you can now automate workflows through the notifications to increase work efficiency. Forecast uses machine learning (ML)

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Shared by AWS Machine Learning March 23, 2021

Favorite In this post, we combine the powers of NVIDIA RAPIDS and Amazon SageMaker to accelerate hyperparameter optimization (HPO). HPO runs many training jobs on your dataset using different settings to find the best-performing model configuration. HPO helps data scientists reach top performance, and is applied when models go into

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Shared by AWS Machine Learning March 20, 2021

Favorite One of the most exciting AWS re:Invent 2020 announcements was a new Amazon SageMaker feature, purpose built to help detect bias in machine learning (ML) models and explain model predictions: Amazon SageMaker Clarify. In today’s world where predictions are made by ML algorithms at scale, it’s increasingly important for

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Shared by AWS Machine Learning March 19, 2021

Favorite The National Football League (NFL) is America’s most popular sports league. Founded in 1920, the NFL developed the model for the successful modern sports league and is committed to advancing progress in the diagnosis, prevention, and treatment of sports-related injuries. Health and safety efforts include support for independent medical

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Shared by AWS Machine Learning March 19, 2021

Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). With a single click, data scientists and developers can quickly spin up Studio notebooks to explore datasets and build models. You can now use Studio notebooks to securely connect to Amazon EMR clusters and

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Shared by AWS Machine Learning March 18, 2021

Favorite Computer vision is a field of artificial intelligence (AI) that is gaining in popularity and interest largely due to increased access to affordable cloud-based training compute, more performant algorithms, and optimizations for scalable model deployment and inference. However, despite these advances in individual AI and machine learning (ML) domains,

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Shared by AWS Machine Learning March 18, 2021

Favorite This blog is co-authored by Sarah Jane Hong CSO, Darryl Barnhart CTO, and Ian Thompson CEO of Latent Space and Prem Ranga of AWS. Latent space is a hidden representation of abstract ideas that machine learning (ML) models learn. For example, “dog,” “flower,” or “door” are concepts or locations

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Shared by AWS Machine Learning March 13, 2021

Favorite This post is a guest joint collaboration by Supratim Banerjee of More Retail Limited and Shivaprasad KT and Gaurav H Kankaria of Ganit Inc. More Retail Ltd. (MRL) is one of India’s top four grocery retailers, with a revenue in the order of several billion dollars. It has a

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Shared by AWS Machine Learning March 13, 2021

Favorite Amazon Textract is a fully managed machine learning (ML) service that automatically extracts printed text, handwriting, and other data from scanned documents that goes beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables. Amazon Textract can detect text in a variety of

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Shared by AWS Machine Learning March 12, 2021