[R] T&C19 - Assets

Leverage ML Training to Improve your Product and Services

Amazon Web Services Resources EMEA

Issue link: https://emea-resources.awscloud.com/i/1140601

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Organizations are using machine learning to improve their products and services Today, machine learning models have developed even further to the point where they are successfully responding to problems with clear goals in an unpredictable environment. Autonomous vehicles are a good example of this: they get from point A to point B safely and at a reasonable speed in the unpredictable environment of the road. 1 A Few Useful Things to Know about Machine Learning, Pedro Domingos, University of Washington, 2012. Over the last decade, machine learning has become good at responding to problems presented in predictable environments and having clearly defined goals. For example, we are all familiar with how machine learning has been successfully applied for use in internet search, spam filters, recommendation systems, ad placement, fraud detection, and stock trading. 1 Machine learning is helping organizations solve real-world problems without having to make significant investments in on-premise technology. Today, even small organizations are harnessing the productivity gains enabled by machine learning models to create new products and innovative business models that are transforming the world of work and customer experiences. Real-world Impacts of Machine Learning It is most apparent that machine learning is having the biggest impact within industries that are already inherently digital in nature. This is in part due to the ready access that these industries have to large data silos, which are therefore easily used for training the machine learning models. These industries have been successful at developing the models that come closest to human decision-making speed and accuracy–which we recognize as 'intelligent'.

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