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Favorite As machine learning (ML) becomes a larger part of companies’ core business, there is a greater emphasis on reducing the time from model creation to deployment. In November of 2019, AWS released the AWS Step Functions Data Science SDK for Amazon SageMaker, an open-source SDK that allows developers to
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Shared by AWS Machine Learning February 13, 2020
Favorite You have many choices for building, training, and deploying machine learning (ML) models. Weighing the financial considerations of different cloud solutions requires detailed analysis. You must consider the infrastructure, operational, and security costs for each step of the ML workflow, as well as the size and expertise of your
Read More Shared by AWS Machine Learning February 12, 2020
Favorite The National Health Care Anti-Fraud Association (NHCAA) estimates that healthcare fraud costs the nation approximately $68 billion annually—3% of the nation’s $2.26 trillion in healthcare spending. This is a conservative estimate; other estimates range as high as 10% of annual healthcare expenditure, or $230 billion. Healthcare fraud inevitably results
Read More Shared by AWS Machine Learning February 11, 2020
Favorite Amazon Personalize is a machine learning service which enables you to personalize your website, app, ads, emails, and more, with custom machine learning models which can be created in Amazon Personalize, with no prior machine learning experience. AWS is pleased to announce that Amazon Personalize now supports ten times
Read More Shared by AWS Machine Learning February 8, 2020
Favorite Enterprises often rely on unique identifiers to look up information on accounts or events. For example, airlines use confirmation codes to locate itineraries, and insurance companies use policy IDs to retrieve policy details. In customer support, these identifiers are the first level of information necessary to address customer requests.
Read More Shared by AWS Machine Learning February 7, 2020
Favorite AWS is pleased to announce a new feature in Amazon Polly called Brand Voice, a capability in which you can work with the Amazon Polly team of AI research scientists and linguists to build an exclusive, high-quality, Neural Text-to-Speech (NTTS) voice that represents your brand’s persona. Brand Voice allows
Read More Shared by AWS Machine Learning February 5, 2020
Favorite Amazon re:MARS 2020 is June 16–19 in Las Vegas, Nevada. Arrive early for our new Developer Day, then join Jeff Bezos, Jon Favreau, and others at Amazon’s event dedicated to machine learning, automation, robotics, and space. re:MARS 2020 brings together leaders and builders across industries for immersive sessions from
Read More Shared by AWS Machine Learning February 5, 2020
Favorite This is a guest post from Millennium Management. In their own words, “Millennium Management is a global investment management firm, established in 1989, with over 2,900 employees and $39.2 billion in assets under management as of August 2, 2019.” Millennium Management is comprised of a large number of specialized
Read More Shared by AWS Machine Learning February 4, 2020
Favorite A critical success factor in machine learning (ML) is the cleanliness and accuracy of training datesets. Training with mislabeled or inaccurate data can lead to a poorly performing model. But how can you easily determine if the labeling team is accurately labeling data? One way is to manually sift
Read More Shared by AWS Machine Learning February 4, 2020
Favorite Amazon Comprehend is a fully managed natural language processing (NLP) service that enables text analytics to extract insights from the content of documents. Amazon Comprehend supports custom classification and enables you to build custom classifiers that are specific to your requirements, without the need for any ML expertise. Previously, custom
Read More Shared by AWS Machine Learning January 30, 2020