![]() These are two different knowledge base capabilities that each involve their own separate research and skill and experience building. It's important to note that for a real understanding of quantum ML, individuals have to have a pretty good grasp of what machine learning algorithms do, and also a certain knowledge of how quantum computing works. ![]() The result may create less theoretical and more practical quantum computing systems. Now, we are seeing some pilot projects at big tech companies where quantum computing is being experimented with in practical ways. The use of quantum computing for machine learning and other processes is becoming more familiar to data scientists and others, as quantum computing goes beyond being a nascent and mainly theoretical technology.
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