AWS Machine Learning Blog
Category: Artificial Intelligence
Amazon EC2 Inf1 instances featuring AWS Inferentia chips now available in five new Regions and with improved performance
Following strong customer demand, AWS has expanded the availability of Amazon EC2 Inf1 instances to five new Regions: US East (Ohio), Asia Pacific (Sydney, Tokyo), and Europe (Frankfurt, Ireland). Inf1 instances are powered by AWS Inferentia chips, which Amazon custom-designed to provide you with the lowest cost per inference in the cloud and lower barriers […]
Read MoreExpanding scientific portfolios and adapting to a changing world with Amazon Personalize
This is a guest blog post by David A. Smith at Thermo Fisher. In their own words, “Thermo Fisher Scientific is the world leader in serving science. Our Mission is to enable our customers to make the world healthier, cleaner, and safer. Whether our customers are accelerating life sciences research, solving complex analytical challenges, improving […]
Read MoreAmazon Textract now available in Asia Pacific (Mumbai) and EU (Frankfurt) Regions
You can now use Amazon Textract, a machine learning (ML) service that quickly and easily extracts text and data from forms and tables in scanned documents, for workloads in the AWS Asia Pacific (Mumbai) and EU (Frankfurt) Regions. Amazon Textract goes beyond simple optical character recognition (OCR) to identify the contents of fields in forms, […]
Read MoreAccessing data sources from Amazon SageMaker R kernels
Amazon SageMaker notebooks now support R out-of-the-box, without needing you to manually install R kernels on the instances. Also, the notebooks come pre-installed with the reticulate library, which offers an R interface for the Amazon SageMaker Python SDK and enables you to invoke Python modules from within an R script. You can easily run machine […]
Read MoreTraining a custom single class object detection model with Amazon Rekognition Custom Labels
Customers often need to analyze their images to find objects that are unique to their business needs. In many cases, this may be a single object, like identifying the company’s logo, finding a particular industrial or agricultural defect, or locating a specific event like a hurricane in satellite scans. In this post, we showcase how […]
Read MoreIncreasing the relevance of your Amazon Personalize recommendations by leveraging contextual information
Getting relevant recommendations in front of your users at the right time is a crucial step for the success of your personalization strategy. However, your customer’s decision-making process shifts depending on the context at the time when they’re interacting with your recommendations. In this post, I show you how to set up and query a […]
Read MoreAmazon Forecast can now use Convolutional Neural Networks (CNNs) to train forecasting models up to 2X faster with up to 30% higher accuracy
We’re excited to announce that Amazon Forecast can now use Convolutional Neural Networks (CNNs) to train forecasting models up to 2X faster with up to 30% higher accuracy. CNN algorithms are a class of neural network-based machine learning (ML) algorithms that play a vital role in Amazon.com’s demand forecasting system and enable Amazon.com to predict […]
Read MoreSecuring Amazon Comprehend API calls with AWS PrivateLink
Amazon Comprehend now supports Amazon Virtual Private Cloud (Amazon VPC) endpoints via AWS PrivateLink so you can securely initiate API calls to Amazon Comprehend from within your VPC and avoid using the public internet. Amazon Comprehend is a fully managed natural language processing (NLP) service that uses machine learning (ML) to find meaning and insights […]
Read MoreMachine learning best practices in financial services
We recently published a new whitepaper, Machine Learning Best Practices in Financial Services, that outlines security and model governance considerations for financial institutions building machine learning (ML) workflows. The whitepaper discusses common security and compliance considerations and aims to accompany a hands-on demo and workshop that walks you through an end-to-end example. Although the whitepaper […]
Read MoreBuild more effective conversations on Amazon Lex with confidence scores and increased accuracy
In the rush of our daily lives, we often have conversations that contain ambiguous or incomplete sentences. For example, when talking to a banking associate, a customer might say, “What’s my balance?” This request is ambiguous and it is difficult to disambiguate if the intent of the customer is to check the balance on her […]
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