The Pyrenn Levenberg-Marquardt training algorithm for Feed-Forward Neural Networks is extremely fast – 0.140 seconds for a Neural controller which must simultaneously balance an inverted pendulum, mounted on a cart, while moving the cart back to the origin – watch the short video below.
In the vast majority of the Neural Network applications that I’ve developed, the training time was a tiny fraction of my time spent on the project. The major time hit on these kinds of efforts is not training time – instead it is the time spent to develop quality and robust training and test data sets (thinking it through and careful analysis of the data – many times this is an iterative process). If this is done correctly, the resultant Neural Networks are built extremely quickly and yield high performance.
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