Writing maintainable code using state machines in Python

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Backend contains data models — which is how your data looks. This can be your Django models or database tables. More often than not, we run into a problem where the model behavior changes faster than the actual data model.

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Model Tuning and the Bias-Variance Tradeoff

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The goal of modeling is to approximate real-life situations by identifying and encoding patterns in data. Models make mistakes if those patterns are overly simple or overly complex. In Part 1, we created a model that distinguishes homes in San Francisco from those in New York.

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