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  1. Developing a robot in Python and MQL5 (Part 1): Data preprocessing

    by , 10-13-2024 at 08:00 AM
    We will look at the development cycle of a trading robot: data collection, processing, sample expansion, feature engineering, model selection and training, creating a trading system via Python, and monitoring trades.

    Working in Python has its own advantages: speed in the field of machine learning, as well as the ability to select and generate features. Exporting models to ONNX requires exactly the same feature generation logic as in Python, which is not easy. That is why I have selected
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