A Technology Broker and Management Company Specializing in KM Systems
Favorite AWS is excited to introduce Amazon SageMaker Operators for Kubernetes, a new capability that makes it easier for developers and data scientists using Kubernetes to train, tune, and deploy machine learning (ML) models in Amazon SageMaker. Customers can install these Amazon SageMaker Operators on their Kubernetes cluster to create
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Shared by AWS Machine Learning December 2, 2019
Favorite If you are interested in how different industries approach KM, here is a new way to differentiate them. Different industries tend to approach KM in different ways, or apply KM in “different flavours.” In September I posted a ternary plot, where different industries were plotted on their relative focus
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Shared by Nick Milton December 2, 2019
Favorite Business in a world of change is a learning race. The winner is the organisation that can develop and mature knowledge more quickly than the competition, bringing new and improved products and processes into the market first, and so gaining First Learner Advantage. Therefore one way of viewing Knowledge
Read More Shared by Nick Milton November 29, 2019
Favorite How do you structure your knowledge store? There are 3 options, but one is far better than the other two in meeting the needs of the knowledge seeker. Image from Robins.af.mil There are three ways to organise your knowledge store. You can organise it by operational units, so that
Read More Shared by Nick Milton November 28, 2019
Favorite We are happy to announce that Amazon Forecast can now generate forecasts at a quantile of your choice. Launched at re:Invent 2018, and generally available since Aug 2019, Forecast is a fully managed service that uses machine learning (ML) to generate highly accurate forecasts, without requiring any prior ML
Read More Shared by AWS Machine Learning November 27, 2019
Favorite Probably the worst place to store project lessons is to leave them in the End of Project Report. Tombstone created using http://tombgen.appspot.com/ I know this is still the default approach for many project organisations, and 19% organisations who run KM programs still use this approach (according to our KM survey).
Read More Shared by Nick Milton November 27, 2019
Favorite Today AWS announced new ways for you to easily add machine learning (ML) predictions to applications and business intelligence (BI) dashboards using relational data in your Amazon Aurora database and unstructured data in Amazon S3, by simply adding a few statements to your SQL (structured query language) queries and
Read More Shared by AWS Machine Learning November 26, 2019
Favorite Organizations in all industries have a large number of physical documents. It can be difficult to extract text from a scanned document when it contains formats such as tables, forms, paragraphs, and check boxes. Organizations have been addressing these problems with Optical Character Recognition (OCR) technology, but it requires
Read More Shared by AWS Machine Learning November 26, 2019
Favorite Machine learning (ML) is routinely used in every sector to make predictions. But beyond simple predictions, making decisions is more complicated because non-optimal short-term decisions are sometimes preferred or even necessary to enable long-term, strategic goals. Optimizing policies to make sequential decisions toward a long-term objective can be learned
Read More Shared by AWS Machine Learning November 26, 2019
Favorite Businesses are increasingly developing per-user machine learning (ML) models instead of cohort or segment-based models. They train anywhere from hundreds to hundreds of thousands of custom models based on individual user data. For example, a music streaming service trains custom models based on each listener’s music history to personalize
Read More Shared by AWS Machine Learning November 26, 2019