Today you hear a lot about machine learning and AI, however, there is also a new wave of interest in the whole neural net world which had a great deal of interest back in the 1980s. Well, its back stronger than ever. Basically, the real reason is that computer hardware/ processors/memory have become very cheap and powerful. Moores Law etc. so today what required some serious computer power can now run their neural nets with lots of low-cost memory and store a great deal of pattern information.
A good video overview of Neural Nets. …. LINK
By Brandon Rohrer
Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a class of machine learning algorithms that:
use a cascade of many layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The algorithms may be supervised or unsupervised and applications include pattern analysis (unsupervised) and classification (supervised).
are based on the (unsupervised) learning of multiple levels of features or representations of the data. Higher level features are derived from lower level features to form a hierarchical representation.
are part of the broader machine learning field of learning representations of data.
learn multiple levels of representations that correspond to different levels of abstraction; the levels form a hierarchy of concepts. WIKI