Favorite The AWS Machine Learning Operations (MLOps) framework is an iterative and repetitive process for evolving AI models over time. Like DevOps, practitioners gain efficiencies promoting their artifacts through various environments (such as quality assurance, integration, and production) for quality control. In parallel, customers rapidly adopt multi-account strategies through AWS
Favorite As humans, we constantly learn from the world around us. We experience inputs that shape our knowledge — including the boundaries of both what we know and what we don’t know. Many of today’s machines also learn by example. However, these machines are typically trained on datasets and information
Favorite Many of our AWS customers provide research, analytics, and business intelligence as a service. This type of research and business intelligence enables their end customers to stay ahead of markets and competitors, identify growth opportunities, and address issues proactively. For example, some of our financial services sector customers do
Favorite It is generally acknowledged that KM requires a culture of trust. But is remote working eroding trust, and what might this do to KM? Trust by Vic on Flickr There are many studies of the links between Knowledge Management and trust (see here, here, and here for example). Without
Favorite Amazon SageMaker Data Wrangler is a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications via a visual interface. Data preparation is a crucial step of the ML lifecycle, and Data Wrangler provides an end-to-end solution
Favorite Amazon SageMaker Data Wrangler makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. Previously, when you created a Data Wrangler data flow, you could choose different export options to easily integrate that data flow into your data
Favorite Amazon SageMaker Data Wrangler is a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and combine features
Favorite Technology trends and advancements in digital media in the past decade or so have resulted in the proliferation of text-based data. The potential benefits of mining this text to derive insights, both tactical and strategic, is enormous. This is called natural language processing (NLP). You can use NLP, for
Favorite All forms of Management involve conversation, and Knowledge Management is no different. The management of intangibles is driven by conversations. Those conversations are focused on the particular intangible in question, and serve to set direction, raise awareness, and lead to action. Risk management is driven by conversations about risk;
Favorite Introducing Knowledge Management is likely to take a decade before it is fully embedded. Here are some benchmark statistics Over the past few decades we have helped many organisations to benchmark their current status of Knowledge Management. They ask for this service for a number of reasons. Sometimes they
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