Describe the challenges of determining the capacity of your current deep learning model and explain how this impacts your optimization strategy. Justify any tradeoffs you’ve made, including the relationship between model complexity and training data size.

The effective capacity of our deep learning model is limited by the capabilities of the optimization algorithm due to its non-convexity and large memory requirements. To optimize performance, we must carefully balance model complexity with the size and quality of our training dataset. This tradeoff allows us to prioritize accuracy over generalization, given the constraints of our system.