Expanding Amazon Lex conversational experiences with US Spanish and British English

Amazon Lex provides the power of automatic speech recognition (ASR) for converting speech to text, along with natural language understanding (NLU) for recognizing user intents. This combination allows you to develop sophisticated conversational interfaces using both voice and text for chatbots, IVR bots, and voicebots. This week, we’re announcing Amazon

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Shared by AWS Machine Learning September 25, 2020

Streamline modeling with Amazon SageMaker Studio and the Amazon Experiments SDK

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, over

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Shared by AWS Machine Learning September 25, 2020

How to recognise a KM opportunity

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 opportunities

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Shared by Nick Milton September 24, 2020

Do learning leaders produce learning organisations?

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 that

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Shared by Nick Milton September 23, 2020

How even 10-year-old space scientists capture their lessons

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 scientists’

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Shared by Nick Milton September 22, 2020