📈 Stock Predictor

A machine learning model that predicts stock prices using a regression approach. This project achieves an 86% regression accuracy within a 0.1 tolerance using a deep learning architecture with:

• ReLU activation
• Mean Squared Scaled (MSS) loss function
• Adam optimizer

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🚀 Features

• Predicts stock prices based on historical data
• Uses a regression model trained on time-series inputs
• High performance with 86% accuracy (tolerance ≤ 0.1)
• Modular and extensible codebase

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🧠 Model Details

• Model Type: Regression (Deep Learning)
• Activation Function: ReLU
• Loss Function: MSS (Mean Squared Scaled)
• Optimizer: Adam
• Evaluation Metric: Accuracy within 0.1 tolerance

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📊 Dataset

The model is trained on a dataset of historical stock prices. The dataset includes:

• Open, High, Low, Close prices
• Volume
• Optional: Technical indicators like SMA, EMA, RSI

📌 Note: Please ensure your data is normalized/scaled appropriately before training.

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Improvements

Planned and possible future enhancements:

🔄 LSTM/Transformer Models: Improve temporal awareness with sequence models

📊 Advanced Metrics: Include MAPE, RMSE, R² score

🌐 Real-Time Data: Integrate Yahoo Finance, Alpha Vantage, or Polygon APIs

🧪 Hyperparameter Tuning: Add Optuna or grid/random search

🧰 Technical Indicators: MACD, Bollinger Bands, RSI, etc.

📉 Backtesting Module: Evaluate predictions with historical strategy tests

📺 Visualization UI: Build dashboard with Streamlit or Dash

📦 Deployment: Export and serve via Flask, FastAPI, or ONNX

🧠 Ensemble Learning: Blend multiple models for robustness

🔁 Checkpoints: Add save/load training checkpoints

🧪 Unit Tests: Ensure stability and correctness ⚙️ AutoML Support: Plug in with H2O, Auto-sklearn, etc.

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Improvements done:

• using advanced evaluation metrics like MSE, MAE and R2

🤝 Contributing Contributions are welcome! To contribute, fork the repo, make changes, and submit a pull request. For major feature proposals, please open an issue first.

📄 License This project is licensed under the MIT License.

💬 Contact For questions, suggestions, or collaborations: 📧 [email protected]

📦 Installation

git clone https://github.com/Indecre/stock-predictor/edit/main/README.md
cd stock-predictor