Neural networks can learn to represent complex relationships between network inputs and outputs. This representational power helps them perform better than traditional machine learning algorithms in computer vision and natural language processing tasks. However, one of the challenges associated with training neural networks is overfitting.
This is a companion discussion topic for the original entry at https://www.pinecone.io/learn/regularization-in-neural-networks/