Explain how representational learning can be applied to this task, and describe the benefits of using deep neural networks over shallow models in terms of statistical efficiency and model size.

Representational learning enables the discovery of high-level, abstract features that capture meaningful relationships between input variables. In this context, deep neural networks can learn to represent complex interactions between product attributes, user demographics, and purchase behavior. By doing so, they achieve exponential gains in statistical efficiency compared to shallow models, allowing for more accurate predictions and improved decision-making at reduced computational cost.