<ul><li>More layers don't always mean better results. A simpler model can often be more cost-effective, interpretable, and operationally efficient.</li><li>Many executives view AI as a black box and perceive deep learning as superior. But explainability and interpretability are crucial for some applications.</li><li>Deep learning requires large datasets, making it unnecessary for companies with limited data points.</li><li>In structured data problems, simpler models often outperform deep learning, especially when relationships between features matter more than pattern recognition.</li></ul>

How to Convince Your Boss That a Simple Model Is Better Than a Deep Neural Network

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