New article Neural Networks Made Easy has been published:
Artificial intelligence is often associated with something fantastically complex and incomprehensible. At the same time, artificial
intelligence is increasingly mentioned in everyday life. News about achievements related to the use of neural networks often
appear in different media. The purpose of this article is to show that anyone can easily create a neural network and use the AI
achievements in trading.
The following neural network definition is provided in Wikipedia:
Artificial neural networks (ANN) are computing systems vaguely inspired by the biological neural networks that constitute animal
brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a
That is, a neural network is an entity consisting of artificial neurons, among which there is an organized relationship. These relations
are similar to a biological brain.
The figure below shows a simple neural network diagram. Here, circles indicate neurons and lines visualize connections between
neurons. Neurons are located in layers which are divided into three groups. Blue indicates the layer of input neurons, which mean an
input of source information. Green and blue are output neurons, which output the neural network operation result. Between them are
gray neurons forming a hidden layer.
Author: Dmitriy Gizlyk
In my opinion it is more realistic to ask MetaQuotes team to implement an easy interface between Keras and MQL5. However, I guess the current
Python interface in MQL5 could be used to some extent to run Keras based models (at least for predictions).
Very interesting article, i really appreciate, Congratulations, but, could you please tell us how can we use these function
classes in a basic model inside OnInit(), OnDeinit(), OnTick() and OnTimer()? How should i call your BPB NeuralNet Functions the right manner inside
an EA code?! Let's suppose a 'XOR Problem', or even a basic structure with last ten ticks value being placed on input, so i can understand how it
works, how to define quantity of hidden layers, where do i insert input's and recall the output?
I've been integrating via Python socket one BPB external code, but i think is reasonable to believe your code could be very effective directly
inside my EA.
Thanks in advance!