In deep learning, architecture engineering is the new feature engineering

Two of the most important aspects of machine learning models are feature extraction and feature engineering. Those features are what supply relevant information to the machine learning models. If the features are few or irrelevant, your model may have a hard time making any useful predictions. If there are too many features, your model will be slow and likely overfit. Humans don't necessarily know what feature representation are best for a given task.