A subset of machine learning based on neural networks with multiple hidden layers. Deep learning models (e.g. CNNs, RNNs, transformers) can automatically learn hierarchical representations from raw data. For forex trading, deep networks (especially recurrent or temporal models like LSTM networks) can capture complex, non-linear patterns in price and indicator time series. In fact, in FX forecasting studies, LSTM networks and other neural nets are among the most commonly used algorithms. Deep learning enables forex robots to analyze intricate market dynamics that simpler models might miss.

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