Incremental learning: Optimizing search relevance at scale using machine learning

Favorite Amazon Kendra is releasing incremental learning to automatically improve search relevance and make sure you can continuously find the information you’re looking for, particularly when search patterns and document trends change over time. Data proliferation is real, and it’s growing. In fact, International Data Corporation (IDC) predicts that 80%

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Shared by AWS Machine Learning December 9, 2020

Model dynamism Support in Amazon SageMaker Neo

Favorite Amazon SageMaker Neo was launched at AWS re:Invent 2018. It made notable performance improvement on models with statically known input and output data shapes, typically image classification models. These models are usually composed of a stack of blocks that contain compute-intensive operators, such as convolution and matrix multiplication. Neo

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Shared by AWS Machine Learning December 9, 2020

Amazon Forecast Weather Index – automatically include local weather to increase your forecasting model accuracy

Favorite We’re excited to announce the Amazon Forecast Weather Index, which can increase your forecasting accuracy by automatically including local weather information in your demand forecasts with one click and at no extra cost. Weather conditions influence consumer demand patterns, product merchandizing decisions, staffing requirements, and energy consumption needs. However,

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Shared by AWS Machine Learning December 9, 2020

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

Favorite 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

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Shared by AWS Machine Learning December 8, 2020