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In recent years, AWS customers have been running machine learning (ML) on an increasing variety of datasets and data sources. Because a large percentage of organizational data is stored in relational databases such as Amazon Aurora, there’s a common need to make this relational data available for training ML models,
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Shared by AWS Machine Learning May 22, 2020
Developers, to help you advance your AI and machine learning (ML) skills with hands-on and engaging learning, the AWS Machine Learning Scholarship Program from Udacity is now open for enrollment. AWS and Udacity are collaborating to educate developers of all skill levels to expand their AWS ML expertise. In this
Read More Shared by AWS Machine Learning May 20, 2020
AWS is excited to announce the general availability of Amazon SageMaker integration in QuickSight. You can now integrate your own Amazon SageMaker ML models with QuickSight to analyze the augmented data and use it directly in your business intelligence dashboards. As a business analyst, data engineer, or data scientist, you
Read More Shared by AWS Machine Learning May 19, 2020
Veeva Systems is a provider of cloud-based software for the global life sciences industry, which offers products that serve multiple domains ranging from clinical, regulatory, quality, and more. Veeva’s Vault Platform manages both content and data in a single platform that allows you to deploy powerful applications that manage the
Read More Shared by AWS Machine Learning May 16, 2020
As the world responds to the ongoing pandemic, it’s more important than ever to accurately access, consume, and analyze information related to COVID-19. Topics about the healthcare crisis permeate many dimensions of our personal and professional lives, through channels as diverse as news reporting, social media, business meetings, radio and
Read More Shared by AWS Machine Learning May 16, 2020
Tens of thousands of customers rely on AWS for building machine learning (ML) applications. Customers like Airbnb and Pinterest use AWS to optimize their search recommendations, Lyft and Toyota Research Institute to develop their autonomous vehicle programs, and Capital One and Intuit to build and deploy AI-powered customer assistants. AWS
Read More Shared by AWS Machine Learning May 15, 2020
As the touchpoints customers use to engage with brands move to an increasingly complex mixture of digital and real-life interactions, you’re faced with the daunting task of delighting your customers with personalized experiences that hit the mark across these channels. Customer expectations are evolving as well. Today’s customers quickly lose
Read More Shared by AWS Machine Learning May 15, 2020
Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as the creation of fake accounts or online payment fraud. Unlike general-purpose machine learning (ML) packages, Amazon Fraud Detector is designed specifically to detect fraud. Amazon Fraud Detector combines your data,
Read More Shared by AWS Machine Learning May 9, 2020
For new home buyers, a common challenge is to understand how to manage their lawn needs effectively. Now imagine if you’re a farmer and have to do this for many acres of land. As a farmer, some of the challenges you’d typically face include the when (when is the right
Read More Shared by AWS Machine Learning May 9, 2020
This is a guest blog post by Sungoh Park, a big data analyst at Lotte Mart. In their own words, “Lotte Mart, a division of Lotte Co., Ltd., is a leading South Korean retailer that sells a variety of groceries, clothing, toys, electronics, and other goods.” Consumers today have many
Read More Shared by AWS Machine Learning May 9, 2020
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