How does PCA interact with neural networks as preprocessing?

PCA can reduce input dimensionality and improve convergence speed in neural networks.

Neural networks can benefit from PCA by reducing input redundancy and noise, leading to faster convergence and reduced overfitting. However, deep networks often learn their own feature representations, making PCA less useful in end-to-end deep learning pipelines.