A relative new concept, deep learning

Deep learning is a relatively new concept for data area.

Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning ) is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data. In a simple case, you could have two sets of neurons: ones that receive an input signal and ones that send an output signal. When the input layer receives an input it passes on a modified version of the input to the next layer. In a deep network, there are many layers between the input and output ( and the payers are not made of neurons but it can help to think of it that way), allowing the algorithms to use multiple processing layers, composed of multiple linear and non-linear transformations. 

Here are  two deep learning examples:

http://www.kdnuggets.com/2015/01/deep-learning-explanation-what-how-why.html

http://www.slideshare.net/0xdata/deep-learning-through-examples

Deep learning tutorials:

http://deeplearning.net/tutorial/deeplearning.pdf

https://cs.stanford.edu/~quocle/tutorial1.pdf

http://ai.stanford.edu/~quocle/tutorial2.pdf