Discussing the article: "Integrating MQL5 with Data Processing Packages (Part 10): Deploying Python AutoML Pipelines for Strategy Testing"

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Check out the new article: Integrating MQL5 with Data Processing Packages (Part 10): Deploying Python AutoML Pipelines for Strategy Testing.

This article presents a reproducible MetaTrader 5 workflow: collect history, engineer nine context features, label simulated EMA crossover trades, train with FLAML, and export to ONNX with fixed opset and plain probabilities. The Expert Advisor loads the model natively, mirrors the Python feature contract, and uses a tunable confidence threshold as a trade filter. Readers can swap signals and features to reuse the same pipeline.

Author: Hlomohang John Borotho