sei-network-price-predictor

SEI Network (SEI) Price Predictor

Model Description

This model is a time-series forecasting model created to predict the future price of SEI Network (SEI) using historical market data.
It identifies patterns from past price movements to estimate possible future trends.

This project is intended for educational and experimental purposes only.

Intended Use

• Cryptocurrency price trend analysis
• Time-series forecasting experiments
• Machine learning research on crypto assets
• Educational demonstrations

Not Intended For

• Real-time or automated trading
• Financial or investment advice
• Guaranteed price predictions

Training Data

The model is trained on historical SEI price data obtained from publicly available cryptocurrency market sources (such as Yahoo Finance or similar providers).

Input features may include:

• Open price
• High price
• Low price
• Close price
• Trading volume

Model Architecture

• Model Type: Time-series forecasting / regression
• Possible models: LSTM, GRU, or classical ML regression
• Framework: Python (TensorFlow / PyTorch / Scikit-learn)

Evaluation Metrics

Model performance is measured using:

• MAE (Mean Absolute Error)
• RMSE (Root Mean Squared Error)

These metrics quantify how close the predictions are to actual prices.

Limitations

• SEI is a relatively volatile cryptocurrency
• Market news and on-chain events are not included
• Sudden price movements may reduce accuracy
• Historical data does not guarantee future results

Ethical Considerations

This model does not use personal data.
Users should be aware of the risks associated with cryptocurrency markets.

How to Use

1. Provide historical SEI price data
2. Preprocess and normalize the data
3. Run the model to generate future price predictions

Disclaimer

This model is provided as-is for educational purposes only.
The author is not responsible for any financial loss arising from its use.

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Author: jomarie04
Project Type: Educational / Experimental