A Technology Broker and Management Company Specializing in KM Systems
Favorite As more organizations move to machine learning (ML) to drive deeper insights, two key stumbling blocks they run into are labeling and lifecycle management. Labeling is the identification of data and adding labels to provide context so an ML model can learn from it. Labels might indicate a phrase
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Shared by AWS Machine Learning April 5, 2022
Favorite There is a clear view than knowledge lies in the “walls” and the “hallways” between the “rooms” of an organisation. Here are some of the implications of this view for Knowledge Management. Image from wikimedia commons This blog post was inspired by a post from Nancy Dixon entitled Where Is
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Shared by Nick Milton April 4, 2022
Favorite For customers looking to implement a GxP-compliant environment on AWS for artificial intelligence (AI) and machine learning (ML) systems, we have released a new whitepaper: Machine Learning Best Practices in Healthcare and Life Sciences. This whitepaper provides an overview of security and good ML compliance practices and guidance on
Read More Shared by AWS Machine Learning April 2, 2022
Favorite Data science and data engineering teams spend a significant portion of their time in the data preparation phase of a machine learning (ML) lifecycle performing data selection, cleaning, and transformation steps. It’s a necessary and important step of any ML workflow in order to generate meaningful insights and predictions,
Read More Shared by AWS Machine Learning April 1, 2022
Favorite Amazon SageMaker Autopilot helps you complete an end-to-end machine learning (ML) workflow by automating the steps of feature engineering, training, tuning, and deploying an ML model for inference. You provide SageMaker Autopilot with a tabular data set and a target attribute to predict. Then, SageMaker Autopilot automatically explores your
Read More Shared by AWS Machine Learning March 30, 2022
Favorite This is blog post is co-written by Theresa Cabrera Menard, an Applied Scientist/Geographic Information Systems Specialist at The Nature Conservancy (TNC) in Hawaii. In recent years, Amazon and AWS have developed a series of sustainability initiatives with the overall goal of helping preserve the natural environment. As part of
Read More Shared by AWS Machine Learning March 30, 2022
Favorite Today, customers interact with brands over an increasingly large digital and offline footprint, generating a wealth of interaction data known as behavioral data. As a result, marketers and customer experience teams must work with multiple overlapping tools to engage and target those customers across touchpoints. This increases complexity, creates
Read More Shared by AWS Machine Learning March 30, 2022
Favorite At Google, Marian Croak’s technical research team, The Center for Responsible AI and Human-Centered Technology, and Jen Gennai’s operations and governance team, Responsible Innovation, collaborate often on creating a fairer future for AI systems. The teams complement each other to support computer scientists, UX researchers and designers, product managers
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Shared by Google AI Technology March 29, 2022
Favorite Carrie Cai, Ben Zevenbergen and Johnny Soraker all work on developing artificial intelligence (AI) responsibly at Google, in the larger research community and across the technology industry. Carrie is a research scientist focusing on human-AI interaction, Ben is an ethicist and policy advisor and Johnny is an AI Principles
Read More Shared by Google AI Technology March 29, 2022
Favorite How do you know your Knowledge Management strategy is in danger of crashing? Here are 6 signs. These 6 danger signs are from a 2009 blog post by Lucas McDonnell, reproduced as a Linked-In Pulse article in 2015, but now available only via this blog. Image from wikimedia commons 1.
Read More Shared by Nick Milton March 28, 2022