TrendMaster leverages cutting-edge Transformer deep learning architecture to deliver highly accurate stock price predictions, empowering you to make informed investment decisions.
- Advanced Transformer-based prediction model
- High accuracy with mean average error of just a few percentage points
- Real-time data visualization
- User-friendly interface
- Customizable model parameters
- Support for multiple stock symbols
TrendMaster stands out as a top-tier tool for financial forecasting by:
- Utilizing a wealth of historical stock data
- Employing sophisticated deep learning algorithms
- Identifying patterns and trends beyond human perception
- Providing actionable insights for smarter investment strategies
Get started with TrendMaster in just one command:
pip install TrendMasterHere's how to integrate TrendMaster into your Python projects:
from trendmaster import TrendMaster
# Initialize TrendMaster
test_symbol = 'SBIN'
tm = TrendMaster(symbol_name_stk=test_symbol)
# Load data
data = tm.load_data(symbol=test_symbol)
# Train the model
tm.train(test_symbol, transformer_params={'epochs': 1})
# Perform inference
predictions = tm.inferencer.predict_future(val_data=data, future_steps=100, symbol=test_symbol)
print(predictions)Our Transformer-based prediction model demonstrates impressive accuracy:
TrendMaster comes with a sleek, user-friendly interface for easy data visualization and analysis:
For detailed documentation, including API reference and advanced usage, please visit our Wiki.
We welcome contributions! Please see our Contributing Guidelines for more details.
This project is licensed under the MIT License - see the LICENSE file for details.
If you find TrendMaster helpful, please consider giving it a star on GitHub. It helps others discover the project and motivates us to keep improving!
For questions, suggestions, or collaboration opportunities, please reach out:
- Website: hjlabs.in
- Email: [email protected]
- LinkedIn: Hemang Joshi
Check out our other exciting projects:
Created with ❤️ by Hemang Joshi