Gartner is predicting a very bright near future for the "Machine learning". 2015 was a peak year of inflated expectations, now, in 2016 is following period of disillusionment and in 2017 should be reached the plateau of productivity. Elsewhere this process usually last for 10 years. One kind of the most popular modern "machine learning" is named "Deep Learning" what is another name for neural networks with little bit more layers and perhaps even with a convolution and/or recursion. The learning of this kinds networks was until now usually based on gradient descent, on slow, iterative, non-reliable process named Backpropagation . That kind of learning is very demanding and extensive. On plain computer can last for hours or even many days and is often unsuccessful concluded. Recently are appeared two algorithms that significantly improve this kind of machine learning: " Bipropagation " and " Border pairs method ". Bipropagat
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