Quantified KM value story number 142; 7-figure increase in sales revenue from simple knowledge sharing meetings

Favorite  HBR have published a case study showing the impact of simple structured knowledge sharing meetings.  Although the article is entitled “how virtual teams can better share knowledge”, the study was held using face to face knowledge transfer meetings, pre-Covid. The study attempted to test whether incentives or structure were

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Shared by Nick Milton November 5, 2020

Creating an intelligent ticket routing solution using Slack, Amazon AppFlow, and Amazon Comprehend

Favorite Support tickets, customer feedback forms, user surveys, product feedback, and forum posts are some of the documents that businesses collect from their customers and employees. The applications used to collect these case documents typically include incident management systems, social media channels, customer forums, and email. Routing these cases quickly

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Shared by AWS Machine Learning November 4, 2020

Explaining Amazon SageMaker Autopilot models with SHAP

Favorite Machine learning (ML) models have long been considered black boxes because predictions from these models are hard to interpret. However, recently, several frameworks aiming at explaining ML models were proposed. Model interpretation can be divided into local and global explanations. A local explanation considers a single sample and answers

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Shared by AWS Machine Learning November 4, 2020

Adding custom data sources to Amazon Kendra

Favorite Amazon Kendra is a highly accurate and easy-to-use intelligent search service powered by machine learning (ML). Amazon Kendra provides native connectors for popular data sources like Amazon Simple Storage Service (Amazon S3), SharePoint, ServiceNow, OneDrive, Salesforce, and Confluence so you can easily add data from different content repositories and

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Shared by AWS Machine Learning November 4, 2020

The organisation after the KM makeover

Favorite What does an organisation look like, when it is fully engaged with Knowledge Management? What will the After shot of the KM make-over look like? House Makeover, from wikimedia commons Introducing KM is an organisational makeover. The “After” shot will not resemble the “Before” shot. If KM is to

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Shared by Nick Milton November 4, 2020

Real-time data labeling pipeline for ML workflows using Amazon SageMaker Ground Truth

Favorite High-quality machine learning (ML) models depend on accurately labeled, high-quality training, validation, and test data. As ML and deep learning models are increasingly integrated into production environments, it’s becoming more important than ever to have customizable, real-time data labeling pipelines that can continuously receive and process unlabeled data. For

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Shared by AWS Machine Learning November 3, 2020