AI Enhanced Neural Network Trader bridges a Python-trained machine learning model with the MQL5 platform to automate trade execution based on price change predictions. The system includes integrated risk management controls such as fixed lot sizing, stop loss, and take profit parameters defined in points. Users can train models using TensorFlow or Scikit-learn and export them to MetaTrader. The repository includes both a primary neural network model and a benchmark logistic regression version for comparison.
ONNX model integration for MetaTrader 5
Python-based neural network training workflow
Automated prediction-based trade execution
Configurable fixed lot sizing and point-based exits
Read from Neural_Network_Trader_EA.mq5. Defaults are the author's; change them in the EA's Inputs tab.
Name
Type
Default
Description
InpLots
double
0.1
Lot size for trades
InpStopLoss
int
50
Stop loss in points
InpTakeProfit
int
100
Take profit in points
How to install it
1Download the sourceUse "Download source (.zip)" above, or clone Anaswar-ash/MT5-PY-AI-Tbot from GitHub, and unzip it.
2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL5/Experts.
3Copy the filesCopy the .mq5 file into Experts.
4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.
5Test before you tradeRun it in the Strategy Tester, then attach it to a demo chart and allow algorithmic trading.
Third-party code. ForexR did not write, test or endorse this EA, and the summary above was generated automatically from its README and code. ForexR lists only repositories with readable source code and never hosts files. Read the code, backtest it and use a demo account first; automated trading can lose money quickly.
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