AWS Machine Learning Blog
Category: Artificial Intelligence
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. […]
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
July 2024: The solution in this blog post is now obsolete with the release of Amazon Lex V2. 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 […]
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, […]
Use Amazon Lex as a conversational interface with Twilio Media Streams
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 platform by providing businesses access to […]
Harvesting success using Amazon SageMaker to power Bayer’s digital farming unit
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 or resource waste. Bayer is using […]
Git integration now available for the Amazon SageMaker Python SDK
Git integration is now available in the Amazon SageMaker Python SDK. You no longer have to download scripts from a Git repository for training jobs and hosting models. With this new feature, you can use training scripts stored in Git repos directly when training a model in the Python SDK. You can also use hosting […]