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Favorite This post is co-authored by Lezgin Bakircioglu, Innovation and Security Manager at Daniel Wellington. In their own words, “Daniel Wellington (DW) is a Swedish fashion brand founded in 2011. Since its inception, it has sold over 11 million watches and established itself as one of the fastest-growing and most
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Shared by AWS Machine Learning June 24, 2021
Favorite Do you ever wonder what goes behind bringing various levels of autonomy to vehicles? What the vehicle sees (perception) and how the vehicle predicts the actions of different agents in the scene (behavior prediction) are the first two steps in autonomous systems. In order for these steps to be
Read More Shared by AWS Machine Learning June 22, 2021
Favorite This post is co-written with Raphey Holmes, Software Engineering Manager, and Jason Mackay, Principal Software Development Engineer, at GoDaddy. GoDaddy is the world’s largest services platform for entrepreneurs around the globe, empowering their worldwide community of over 20 million customers—and entrepreneurs everywhere—by giving them all the help and tools
Read More Shared by AWS Machine Learning June 22, 2021
Favorite We are living in a digital age. Information that used to be spread by printouts is disseminated at unforeseen speeds through digital formats. In parallel to the inventions of new types of media, an increasing number of archives and libraries are trying to create digital repositories with new technologies.
Read More Shared by AWS Machine Learning June 21, 2021
Favorite Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. In previous posts, we demonstrated how customers can use the automatic model training capability of Amazon Redshift to train their classification and regression models. Redshift ML provides several capabilities for data
Read More Shared by AWS Machine Learning June 17, 2021
Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). Studio provides a single web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. You can quickly upload data, create new
Read More Shared by AWS Machine Learning June 16, 2021
Favorite Amazon Lookout for Metrics uses machine learning (ML) to automatically detect and diagnose anomalies (outliers from the norm) without requiring any prior ML experience. Amazon CloudWatch provides you with actionable insights to monitor your applications, respond to system-wide performance changes, optimize resource utilization, and get a unified view of
Read More Shared by AWS Machine Learning June 15, 2021
Favorite Several recent surveys show that more than 80% of consumers prefer spending with a credit card over cash. Thanks to advances in AI and machine learning (ML), credit card fraud can be detected quickly, which makes credit cards one of the safest and easiest payment methods to use. The
Read More Shared by AWS Machine Learning June 14, 2021
Favorite To help you fast track your company’s adoption of machine learning (ML), AWS offers educational solutions for developers to get hands-on experience. We like to think of these programs as a fun way for developers to build their skills using ML technologies in real world scenarios. In this post,
Read More Shared by AWS Machine Learning June 10, 2021
Favorite Amazon Redshift ML simplifies the use of machine learning (ML) by using simple SQL statements to create and train ML models from data in Amazon Redshift. You can use Amazon Redshift ML to solve binary classification, multi-class classification, and regression problems and can use either AutoML or XGBoost directly.
Read More Shared by AWS Machine Learning June 10, 2021