Favorite AWS customers often choose to run machine learning (ML) inferences at the edge to minimize latency. In many of these situations, ML predictions must be run on a large number of inputs independently.  For example, running an object detection model on each frame of a video. In these cases, parallelizing

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Shared by AWS Machine Learning August 21, 2019

Favorite Spectral MD, Inc. is a clinical research stage medical device company that describes itself as “breaking the barriers of light to see deep inside the body.” Recently designated by the FDA as a “Breakthrough Device,” Spectral MD provides an impressive solution to wound care using cutting edge multispectral imaging

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Shared by AWS Machine Learning August 16, 2019

Favorite The AWS DeepRacer League is the world’s first global autonomous racing league, open to anyone. Developers of all skill levels can get hands-on with machine learning in a fun and exciting way, racing for prizes and glory at 21 events globally and online using the AWS DeepRacer console. The

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Shared by AWS Machine Learning August 15, 2019

Favorite Today, many companies use one-time passwords (OTP) to authenticate users. An application asks you for a password to proceed. This password is sent to you via text message to a registered phone number. You enter the password to authenticate. It is an easy and secure approach to verifying user

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Shared by AWS Machine Learning August 15, 2019

Favorite Anyone who has tried building a bot to support interactions knows that managing the conversation flow can be tricky. Real users (people who obviously haven’t rehearsed your script) can digress in the middle of a conversation. They could ask a question related to the current topic or take the

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Shared by AWS Machine Learning August 9, 2019

Favorite The Amazon ML Solutions Lab worked with Kinect Energy recently to build a pipeline to predict future energy prices based on machine learning (ML). We created an automated data ingestion and inference pipeline using Amazon SageMaker and AWS Step Functions to automate and schedule energy price prediction. The process

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Shared by AWS Machine Learning August 9, 2019

Favorite Launched at AWS re:Invent 2018, Amazon SageMaker Ground Truth enables you to efficiently and accurately label the datasets required to train machine learning (ML) systems. Ground Truth provides built-in labeling workflows that take human labelers step-by-step through tasks and provide tools to help them produce good results. Built-in workflows

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Shared by AWS Machine Learning August 8, 2019

Favorite Businesses use the Twilio platform to build new ways to communicate with their customers: whether it’s fully automating a restaurant’s food orders with a conversational Interactive Voice Response (IVR) or building a next generation advanced contact center. With the launch of Media Streams, Twilio is opening up their Voice

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Shared by AWS Machine Learning August 7, 2019

Favorite By the year 2050, our planet will need to feed ten billion people. We can’t expand the earth to create more agricultural land, so the solution to growing more food is to make agriculture more productive and less resource-dependent. In other words, there is no room for crop losses

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Shared by AWS Machine Learning August 6, 2019

Favorite With a few clicks in the Amazon SageMaker console or a few one-line API calls, you can now quickly search, filter, and sort your machine learning (ML) experiments using key model attributes, such as hyperparameter values and accuracy metrics, to help you more quickly identify the best models for

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Shared by AWS Machine Learning August 3, 2019