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

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- So next, after the design of the system, we're going to have to deal with how the system is going to be constructed or how it's going to be built. So ultimately this is about configuration. This is about your ability to understand the capabilities of the machine learning system, in this case Azure Machine Learning, and its configuration to the right purposes and how you're going to leverage it. Ultimately, we need to add behavior or turn it into a core application. So, how are we going to do that problematically. Are we going to leverage the visual interface or the programmatic interface, for instance. We're obviously dealing with data. Which databases are going to be leveraged and ultimately how the schemas are going to be structured within those systems. And then the ability to, in essence, test the machine learning based systems and do tuning. We're going to find that in many instances it doesn't carry out the…

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