There is a class of computational problems that is not easy to solve with conventional methods.
Problems involving cognitive ability typical of humans, such as image and speech recognition if faced with deterministic algorithms may require a considerable effort to be solved.
For example, handwritten digits recognition is not a challenge for a human being, but it can be a complex task for a computer.
Machine learning algorithms, including ANN inspired by biological neural network, is a complex adaptive system that can change its internal structure based on the information flowing through it. Learning from it. They basically consist in a set of mathematical learning models and algorithms, used for example to approximate functions that can depend on a large number of inputs and are generally unknown, providing good solutions to broad spectrum of applications including predictive analytics, medical diagnosis, economic forecasts, sport betting, image and speech recognition, natural language processing, etc., because they process information in a similar way the human brain does and can be used to extract patterns that are too complex to be inferred by other techniques.
The prefix "nu" does not mean "new", but it comes from a namespace that I often use in the source code, with different meaning, but it sounded good enough to be used.
It is a version of the standard of the C++ programming language approved by ISO on 12 August 2011.
C++11 includes several additions to the core language and extends the C++ Standard Library.
If you are interested in more information on C++11, please read this