# TrendMaster **Repository Path**: turbock/TrendMaster ## Basic Information - **Project Name**: TrendMaster - **Description**: No description available - **Primary Language**: Python - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-07-16 - **Last Updated**: 2025-07-16 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # TrendMaster: Advanced Stock Price Prediction using Transformer Deep Learning [![Python Version](https://img.shields.io/badge/python-3.7%2B-blue)](https://www.python.org/downloads/) [![License](https://img.shields.io/badge/license-MIT-green)](https://opensource.org/licenses/MIT) [![GitHub Stars](https://img.shields.io/github/stars/hemangjoshi37a/TrendMaster?style=social)](https://github.com/hemangjoshi37a/TrendMaster/stargazers) [![GitHub Forks](https://img.shields.io/github/forks/hemangjoshi37a/TrendMaster?style=social)](https://github.com/hemangjoshi37a/TrendMaster/fork) [![GitHub Issues](https://img.shields.io/github/issues/hemangjoshi37a/TrendMaster)](https://github.com/hemangjoshi37a/TrendMaster/issues) TrendMaster is an advanced stock price prediction library that leverages Transformer deep learning architecture to deliver highly accurate predictions, empowering investors with data-driven insights. ## Table of Contents - [Features](#features) - [Why TrendMaster?](#why-trendmaster) - [Installation](#installation) - [Quick Start](#quick-start) - [Sample Results](#sample-results) - [User Interface](#user-interface) - [Documentation](#documentation) - [Contributing](#contributing) - [License](#license) - [Show Your Support](#show-your-support) - [Contact](#contact) - [More from HJ Labs](#more-from-hj-labs) - [Try Our Algo Trading Platform hjAlgos](#try-our-algo-trading-platform-hjalgos) ## 🚀 Features - **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** ## 📊 Why TrendMaster? 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 ## 🛠️ Installation Get started with TrendMaster in just one command: ```bash pip install TrendMaster ``` ## 📈 Quick Start Here's how to integrate TrendMaster into your Python projects: ```python # Example usage of merged_module.py from trendmaster import ( DataLoader, TransAm, Trainer, Inferencer, set_seed, plot_results, plot_predictions ) import pyotp # Set seed for reproducibility set_seed(42) user_id = 'YOUR_ZERODHA_USER_ID' password = 'YOUR_ZERODHA_PASSWORD' # Replace with your password totp_key = 'YOUR_ZERODHA_2FA_KEY' # Replace with your TOTP secret key # Generate the TOTP code for two-factor authentication totp = pyotp.TOTP(totp_key) twofa = totp.now() # Initialize DataLoader and authenticate data_loader = DataLoader() kite = data_loader.authenticate(user_id=user_id, password=password, twofa=twofa) # Prepare data train_data, test_data = data_loader.prepare_data( symbol='RELIANCE', from_date='2023-01-01', to_date='2023-02-27', input_window=30, output_window=10, train_test_split=0.8 ) import torch # Initialize model, trainer, and train the model device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') print(f'Training on {device} device.') model = TransAm(num_layers=2, dropout=0.2).to(device) trainer = Trainer(model, device, learning_rate=0.001) train_losses, val_losses = trainer.train(train_data, test_data, epochs=2, batch_size=64) # Save the trained model trainer.save_model('transam_model.pth') # Initialize inferencer and make predictions inferencer = Inferencer(model, device, data_loader) predictions = inferencer.predict( symbol='RELIANCE', from_date='2023-02-27', to_date='2023-12-31', input_window=30, future_steps=10 ) # Evaluate the model test_loss = inferencer.evaluate(test_data, batch_size=32) ``` ## 📈 Backtest Results Evaluate the performance of TrendMaster using our comprehensive backtesting framework. Our Transformer-based model has been rigorously tested to ensure reliability and accuracy in diverse market conditions. ### 🔍 View Backtest Results Explore detailed backtest results on our [hjAlgos Backtest Platform](https://hjalgos.hjlabs.in/backtest/). ![bokeh_plot (35)](https://github.com/user-attachments/assets/c2e7a910-3aa8-494d-958e-48199cf85459) *Sample Backtest Performance Chart* ## 📊 Sample Results Our Transformer-based prediction model demonstrates impressive accuracy: ![Transformer-Future200](https://user-images.githubusercontent.com/12392345/125791397-a344831b-b28c-4660-b295-924cb7123872.png) ## 🖥️ User Interface TrendMaster comes with a sleek, user-friendly interface for easy data visualization and analysis: ![TrendMaster UI](https://user-images.githubusercontent.com/12392345/125791827-a4597af0-1292-42d0-9eb1-118d7ef64cbc.png) ## 📘 Documentation For detailed documentation, including API reference and advanced usage, please visit our [Wiki](https://github.com/hemangjoshi37a/TrendMaster/wiki). ## 🤝 Contributing We welcome contributions! Please see our [Contributing Guidelines](CONTRIBUTING.md) for more details. ## 📝 License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. ## 🌟 Show Your Support 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! [![GitHub Star History](https://api.star-history.com/svg?repos=hemangjoshi37a/TrendMaster&type=Date)](https://star-history.com/#hemangjoshi37a/TrendMaster&Date) ## 📫 Contact For questions, suggestions, or collaboration opportunities, please reach out: - Website: [hjlabs.in](https://hjlabs.in/) - Email: [hemangjoshi37a@gmail.com](mailto:hemangjoshi37a@gmail.com) - LinkedIn: [Hemang Joshi](https://www.linkedin.com/in/hemang-joshi-046746aa) ## 🔗 More from HJ Labs Check out our other exciting projects: - [pyPortMan](https://github.com/hemangjoshi37a/pyPortMan) - [AutoCut](https://github.com/hemangjoshi37a/AutoCut) - [TelegramTradeMsgBacktestML](https://github.com/hemangjoshi37a/TelegramTradeMsgBacktestML) ## 📫 Try Our Algo Trading Platform hjAlgos Ready to elevate your trading strategy? Try Our AlgoTrading Platform --- Created with ❤️ by [Hemang Joshi](https://github.com/hemangjoshi37a)