Favorite The modeling phase is a highly iterative process in machine learning (ML) projects, where data scientists experiment with various data preprocessing and feature engineering strategies, intertwined with different model architectures, which are then trained with disparate sets of hyperparameter values. This highly iterative process with many moving parts can,
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Shared by AWS Machine Learning September 25, 2020
Favorite In this post, we show you how to select the right metadata for your use case when building a recommendation engine using Amazon Personalize. The aim is to help you optimize your models to generate more user-relevant recommendations. We look at which metadata is most relevant to include for
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Shared by AWS Machine Learning September 25, 2020
Favorite In recent years, businesses are increasingly looking for ways to integrate the power of machine learning (ML) into business decision-making. This post demonstrates the use case of creating an optimal incentive program to offer customers identified as being at risk of leaving for a competitor, or churning. It extends
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Shared by AWS Machine Learning September 25, 2020
Favorite Optical character recognition (OCR) technology, which enables extracting text from an image, has been around since the mid-20th century, and continues to be a research topic today. OCR and document understanding are still vibrant areas of research because they’re both valuable and hard problems to solve. AWS has been
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Shared by AWS Machine Learning September 25, 2020
Favorite Implementing Knowledge Management involves identifying opportunities where KM can help the business. But how do you spot these opportunities? My Name is Opportunity, by One Way Stock, on Flickr Implementing KM is not just a case of top-down roll-out of a Knowledge Management framework, but should involve looking for
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Shared by Nick Milton September 24, 2020
Favorite University of Illinois, Urbana Champaign (UIUC) has partnered with the Amazon Machine Learning Solutions Lab to help UIUC football coaches prepare for games more efficiently and improve their odds of winning. Previously, coaches prepared for games by creating a game planning sheet that only featured types of plays for
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Shared by AWS Machine Learning September 24, 2020
Favorite Do learning organisations require learning leaders? Almost certainly they do, but will learning leaders require their organisations to learn as well? How well do leaders learn? There is the stereotype of the bull-headed CEO, hanging on to their dream, forging ahead single-mindedly until they dominate the industry. But is
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Shared by Nick Milton September 23, 2020
Favorite Here is an interesting story about a couple of scientists who created a craft which reached the edge of space, and who (as good knowledge workers should) captured their lessons learned afterwards. The surprise is that they were only 8 and 10 years old at the time! The young
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Shared by Nick Milton September 22, 2020
Favorite The knowledge workers represent one of your two main stakeholder groupings for Knowledge Management implementation. But who exactly are they? Image from CreazillaPublic domain licence Firstly we can eliminate from the group “knowledge worker” anyone who is purely a manual worker – someone who follows orders or preassigned inflexible
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Shared by Nick Milton September 21, 2020
Favorite Just incentivising knowledge publishing risks drowning the organisation in trivia. Social media overloadby Mark Smiciklas on Flickr I once had a conversation with a knowledge manager, who explained to me the incentive system they used for KM. My heart sank. In this particular organisation, people were incentivised to publish
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Shared by Nick Milton September 18, 2020
Shared by AWS Machine Learning September 25, 2020
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