Big Picture Design

A strong big-picture system design is crucial for success in machine learning system design interviews. It's not about drawing a perfect diagram immediately, but about demonstrating an understanding of the system's components and their interactions. Here are the core points from this lesson:

• Identify the inputs and outputs of the system during the alignment phase to establish a foundation for building the diagram
• Start with the user and the service, then progressively add components, especially those involving machine learning, to illustrate the flow of data and processes
• Break down machine learning components beyond a single "ML system" box to show the different stages and types of models involved
• Include essential infrastructure elements, such as feature stores, to demonstrate a comprehensive understanding of the system
• Iterate on the diagram, adding or modifying components as a deeper understanding of the problem and its requirements develops

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