Artificial Intelligence and Neural Networks

Artificial intelligence and neural networks are often a subject of fascination. However, their core is not as mysterious as perceived. A neural network is a thoughtfully designed program that aims to achieve specific goals. Understanding this requires examining the algorithms and mathematical equations such as linear regression used in these networks.

Linear regression is an affine function, essential for neural network development. When constructing a neural network, it’s crucial to find values that best fit the data set, thus simplifying computation and optimizing performance.

In these articles, the focus will be on demonstrating these processes using MQL5 exclusively. This approach will illustrate that the right understanding and method can be applied across various programming languages, showcasing the c...
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Discover the fundamentals of neural networks and their vast potential in trading algorithm development. This article delves into the architecture of multilayer perceptrons (MLP) and deep neural networks, highlighting their strengths in task complexity and practical applications like stock market predictions. Learn about feedforward, convolutional, and recurrent neural networks, and understand the role of activation functions such as ReLU, Sigmoid, TanH, and SoftMax. By exploring input, hidden, and output layers, this piece provides insights into crafting effective neural network architectures, essential for MetaTrader 5 developers pursuing advancements in algorithmic trading solutions. Ideal for both seasoned developers and those looking to enhance their MQL5 coding skills.

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