This project combines supervised and self-supervised learning with RPA and broker automation to build an AI trading strategy.
- ๐ LSTM-based supervised learning
- ๐ Contrastive predictive coding for self-supervised learning
- ๐ค Alpaca integration for automated trading
- ๐ Technical indicators and feature engineering
- โ๏ธ RPA scheduler for real-time trade execution
- ๐ฌ Backtesting and hyperparameter tuning
git clone https://github.com/yourusername/rpa-ml-trading-bot.git
cd rpa-ml-trading-bot
pip install -r requirements.txt- Use
fetch_data.pyto load market data. - Train models via
train_model.py. - Run
schedule_jobs.pyto automate trading. - Serve models with
model_api.py.
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