AI + Trading Tutorials

How to pull price history with the Deriv API in Python: ticks_history, candles (OHLC) by granularity, and live ticks via subscribe. Ready-to-use code.

How to use ta.supertrend in Pine Script v5: syntax, what it returns (line and direction), and ready-to-paste TradingView code with buy and sell signals.

A practical reference for the iqoptionapi Python library: connect, read candles, buy and read the result with check_win_v4. Code example plus a free open-source bot.

Meet the IaTraderPro Bot: open-source binary options bot for Quotex and IQ Option, 100% free. 9 ready strategies, visual browser dashboard, and you can modify it by chatting with ChatGPT or Claude — no coding required.

Five ML architectures for trading exportable to ONNX: Random Forest, XGBoost, 1D CNN, LSTM/GRU, Transformer. When to use each + export code.

Practical comparison of 3 ways to run AI in MT5 Expert Advisor: native ONNX with CUDA (recommended 2026), Python server via socket, and C++ DLL.

Complete reference of native MQL5 ONNX functions updated for Build 5572: OnnxCreate, OnnxRun, new ONNX_LOGLEVEL_* flags, CUDA GPU support and error codes.

Step-by-step tutorial to export Python models (Sklearn Random Forest and PyTorch LSTM) to ONNX format and consume in MT5 Expert Advisor. Complete code + Strategy Tester validation.

2026 pillar guide updated for MT5 Build 5572: native CUDA GPU support, new ONNX_LOGLEVEL_* logging system, Python -> ONNX -> EA workflow, supported frameworks and honest limitations.