AWS Machine Learning Blog

Speed up training on Amazon SageMaker using Amazon FSx for Lustre and Amazon EFS file systems

April 2021 – The Amazon FSx section of this post has been updated to cover changes introduced to mount point names with scratch_2 and persistent_1 deployment options. Amazon SageMaker provides a fully managed service for data science and machine learning workflows. One of the most important capabilities of Amazon SageMaker is its ability to run fully […]

Serving deep learning at Curalate with Apache MXNet, AWS Lambda, and Amazon Elastic Inference

This is a guest blog post by Jesse Brizzi, a computer vision research engineer at Curalate. At Curalate, we’re always coming up with new ways to use deep learning and computer vision to find and leverage user-generated content (UGC) and activate influencers. Some of these applications, like Intelligent Product Tagging, require deep learning models to […]

Making daily dinner easy with Deliveroo meals and Amazon Rekognition

When Software Engineer Florian Thomas describes Deliveroo, he is talking about a rapidly growing, highly in-demand company. Everyone must eat, after all, and Deliveroo is, in his words, “on a mission to transform the way you order food.”  Specifically, Deliveroo’s business is partnering with restaurants to bring customers their favorite eats, right to their doorsteps. […]

Parallelizing across multiple CPU/GPUs to speed up deep learning inference at the edge

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 ML inferences across all available CPU/GPUs […]

Modernizing wound care with Spectral MD, powered by Amazon SageMaker

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 and deep learning technologies. This Dallas-based […]

Authenticate users with one-time passwords in Amazon Lex chatbots

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 identity. In this blog post, we’ll […]

AWS DeepRacer League weekly challenges – compete in the AWS DeepRacer League virtual circuit to win cash prizes and a trip to re:Invent 2019!

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 Virtual Circuit launched at the end […]

Kinect Energy uses Amazon SageMaker to Forecast energy prices with Machine Learning

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 makes special use of the Amazon […]

Managing Amazon Lex session state using APIs on the client

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 conversation in an entirely new direction. […]

Adding a data labeling workflow for named entity recognition with Amazon SageMaker Ground Truth

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 are currently available for object detection, […]