Feature Engineering For Deep Learning (IT Best Kept Secret Is Optimization)

Feature engineering and feature extraction are key, and time consuming, parts of the machine learning workflow. They are about transforming training data, augmenting it with additional features, in order to make machine learning algorithms more effective. Deep learning is changing that according to its promoters. With deep learning, one can start with raw data as features will be automatically created by the neural network when it learns. The feature engineering approach was the dominant approach till recently when deep learning techniques started demonstrating recognition performance better than the carefully crafted feature detectors.