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

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- [Instructor] So once we define the requirements and have done the design, we need to determine how we're going to build the application. So, ultimately this is asking yourself a few core questions. First and foremost, how we're going to configure the system, what enabling technology we're going to use, what's our approach to be? We need to figure out how we're going to provide behavior to the machine learning-based systems in terms of programming, perhaps programming languages. Are we going to leverage Python, JavaScript, something else? We need to figure out how the data is going to be physically implemented, how it's going to be structured, and we need to figure out how we're going to test the environment, how we're going to test the machine learning-based systems and knowledge base as well as tune it. The ability to adjust it or fine-tune it as to what it needs to do during operations. And then if we're a modern…

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