From the course: Leveraging Cloud-Based Machine Learning on AWS: Real-World Applications

AI on AWS - Amazon Web Services (AWS) Tutorial

From the course: Leveraging Cloud-Based Machine Learning on AWS: Real-World Applications

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AI on AWS

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- [Instructor] So, what does artificial intelligence mean to the world of Amazon Web Services or cloud computing in general? Well, AI systems, sometimes called machine learning and deep learning systems as well, they make your system think. Ultimately, you're able to gather knowledge over time. So, we're able to vine learning systems to traditional applications that typically didn't leverage artificially intelligent systems and we're also able to find patterns in mass amounts of data. The ability to think through what's occurring within the data that's really coming to some conclusions that we should be aware of. And ultimately, the ability to automate things that aren't currently automated. We may have understandable knowledge skills today and we're leveraging people who understand those skills and we're able to hand off some of that work to artificially intelligent systems. So the idea is that we're looking at two categories of artificially intelligent cloud services on AWS. And we have the non native which are systems that are used within Amazon Web Services and outside Amazon Web Services. Those include TensorFlow, PyTorch, and Apache MXNet. In this course we're going to focus on Amazon Web Services native cloud services and specifically that's going to be Amazon SageMaker.

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