Deep learning – is a machine learning methodology where a system learns the patterns in data by automatically learning a hierarchical layer of features. In deep learning, data is typically pushed through a "deep" stack of activation layers. Each layer builds a representation of the data, with subsequent layers using the features of the previous layer to build more complex representations. The output of the final layer is mapped to a category to which the data should belong. Getting this final mapping correct is the objective of a deep learning algorithm.
At first Deep Learning provides the computer program is with training data, for example images that have been labeled with meta tags. The algorithm uses this information to build a progressively more accurate predictive capability. In contrast, shallow machine learning approaches rely on a substantial amount of feature engineering processes carried out by humans before a model can learn the relationship between features; in deep learning, however, the system acquires the features and their relationships simultaneously.
