Why neural networks?
Neural networks have been around for many years, and they have gone through several periods during which they have fallen in and out of favor. However, in recent years, they have steadily gained ground over many other competing machine learning algorithms. The reason for this is that advanced neural net architecture has shown accuracy in many tasks that has far surpassed that of other algorithms. For example, in the field of image recognition, accuracy may be measured against a database of 16 million images named ImageNet.
Prior to the introduction of deep neural nets, accuracy had been improving at a slow rate, but after the introduction of deep neural networks, accuracy dropped from an error rate of 40% in 2010 to less than 7% in 2014, and this value is still falling. The human recognition rate is still lower, but only at about 5%. Given the success of deep neural networks, all entrants to the ImageNet competition in 2013 used some form of deep neural network. In...
