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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
Favorite Amazon SageMaker Neo enables developers to train machine learning (ML) models once and optimize them to run on any Amazon SageMaker endpoints in the cloud and supported devices at the edge. Since Neo was first announced at re:Invent 2018, we have been continuously working with the Neo-AI open-source communities
Read More Shared by AWS Machine Learning December 9, 2020
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,
Read More Shared by AWS Machine Learning December 9, 2020
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
Read More Shared by AWS Machine Learning December 8, 2020
Favorite Chatbots have become an increasingly important channel for businesses to service their customers. Chatbots provide 24/7 availability and can help customers interact with brands anywhere, anytime and on any device. To effectively utilize chatbots, they must be built with good design, development, test, and deployment practices. This post provides
Read More Shared by AWS Machine Learning December 5, 2020
Favorite In today’s world, being able to quickly bring on-premises machine learning (ML) models to the cloud is an integral part of any cloud migration journey. This post provides a step-by-step guide for launching a solution that facilitates the migration journey for large-scale ML workflows. This solution was developed by
Read More Shared by AWS Machine Learning December 4, 2020
Favorite Yesterday at AWS re:Invent 2020, we announced AWS Panorama, a new machine learning (ML) Appliance and SDK, which allows organizations to bring computer vision (CV) to their on-premises cameras to make automated predictions with high accuracy and low latency. In this post, you learn how customers across a range
Read More Shared by AWS Machine Learning December 3, 2020
Favorite As organizations continue to adopt microservices, the number of disparate services that contribute to delivering applications increases, driving the scope of signals that on-call teams monitor to grow exponentially. It’s becoming more important than ever for these teams to have tools that can quickly and autonomously detect anomalous behaviors
Read More Shared by AWS Machine Learning December 3, 2020
Favorite Statistical analysis and simulation are prevalent techniques employed in various fields, such as healthcare, life science, and financial services. The open-source statistical language R and its rich ecosystem with more than 16,000 packages has been a top choice for statisticians, quant analysts, data scientists, and machine learning (ML) engineers.
Read More Shared by AWS Machine Learning December 3, 2020
Favorite AWS DeepRacer allows you to get hands on with machine learning (ML) through a fully autonomous 1/18th scale race car driven by reinforcement learning, a 3D racing simulator on the AWS DeepRacer console, a global racing league, and hundreds of customer-initiated community races. The action is already underway at
Read More Shared by AWS Machine Learning December 2, 2020