We have not attempted to write another neural net tutorial. There are many already on the Internet, which we would only plagiarize anyway. Its learning algorithm is a BackProp, with either incremental or batch learning, using the popular Generalized Delta Rule, i.e. with learning rate and momentum. There are we believe two main benefits in using this program, namely its versatility, and access to source code.
Many commercial software give the user very little to play with.
It can indeed be difficult for most traders to fully comprehend algorithms details, and there is maybe no real need to as long as the neural net is used in circumstances it was designed for. They are more complex to program, but appear to be easier to use. It is true that the BackProp algorithm requires setting a learning rate, as well as a momentum factor to guide its training process, whereas other algorithms like those cited above, don't. However, the real complexity lies primarily in setting many training parameters other than the learning rate, like the optimal size of the neural net, or when to stop training. The good old BackProp is still pretty good once one has experimented the problem and come up with a good learning rate.