From the course: Cloud Quantum Computing Essentials
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Explore quantum ML methods: Classification
From the course: Cloud Quantum Computing Essentials
Explore quantum ML methods: Classification
- [Instructor] Because there are some aspects of working with QML that are unique to the ML space, I wanted to start with an example that was somewhat simpler than neural networks in terms of machine learning. I'm starting with this example from Quantum Inspire, which is classification. Again, this is really clearly written assuming that most of you know what a classifier is. If not, it's basically an algorithm which labels data, often images, the sort of quintessential is, is this photo a cat or a dog, and there are many, many others but this is the sort of canonical example. So, of course all that information, whether it's a photo or whether it's in some other format has to be encoded. And this example actually shows quite nicely that there is an additional level of complexity when you're working with QML because you have to encode the data that is going to be used as example data into a quantum format. So, it goes on to…
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