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Cryptocurrency Price Prediction Dashboard

Project Overview

This project is a web application for predicting cryptocurrency prices using LSTM models. The dashboard is built using Plotly Dash and provides visualization of actual and predicted closing prices for Bitcoin (BTC-USD), Ethereum (ETH-USD), and Cardano (ADA-USD).

Demo video here: https://youtu.be/6Wz7xLmob4k?si=WuhEe0vOHSVZTMbm

The project is inspired by a tutorial on stock price prediction by Data Flair.

Student Information

  • Student ID: 20120454
  • Name: Cong-Dat Le
  • Module: Advanced Topics in Software Development Technology
  • Instructor: M.S. Van-Quy Tran, M.S. Duy-Quang Tran, M.S. Nguyen-Kha Do

Technologies Used

  • Python
  • Plotly Dash
  • LSTM (Long Short-Term Memory) Model
  • Pandas
  • NumPy
  • Keras
  • TensorFlow

Project Structure

├── app.py                              # Main application script for the Dash web app.
├── cryptocurrency_prediction.ipynb     # Jupyter notebook for trainning the LSTM model.
├── cryptocurrency_data.ipynb           # Jupyter notebook for getting cryptocurrency price data from Yahoo Finance.
├── requirements.txt                    # List of Python dependencies required for the project.
├── csvdata                             # Directory containing CSV data files for cryptocurrencies.
│   ├── BTC-USD.csv                     # Historical price data for Bitcoin.
│   ├── ETH-USD.csv                     # Historical price data for Ethereum.
│   ├── ADA-USD.csv                     # Historical price data for Cardano.
│   └── all_data.csv                    # All data in one file.
├── saved_model.h5                      # Trained LSTM model file.
├── saved_model.keras                   # Trained LSTM model file.
├── README.md                           # Project overview, installation instructions, and usage guide.
└── LICENSE                             # This project is licensed under the MIT License

Installation

  1. Clone the repository:

    git clone https://github.com/Dat-TG/Cryptocurrency-Price-Prediction.git
cd Cryptocurrency-Price-Prediction

  2. Create a virtual environment and activate it:

    python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

  3. Install the dependencies:

    pip install -r requirements.txt

Running the Application

  1. Ensure your model file (saved_model.h5) and CSV data files are in the appropriate directories.

  2. Run the Dash application:

    python app.py

  3. Open your web browser and go to http://127.0.0.1:8050/ to view the dashboard.

Deployment

The project is deployed on Render and can be accessed at https://cryptocurrency-price-prediction.onrender.com/.

To deploy the application to Render:

  1. Ensure your project contains requirements.txt.

  2. Push your code to a GitHub repository.

  3. Create a new Web Service on Render and connect it to your GitHub repository.

  4. Render will automatically detect the requirements.txt and use it to build and run your app.

Usage

  • The dashboard contains three tabs for Bitcoin (BTC-USD), Ethereum (ETH-USD), and Cardano (ADA-USD), and one tab for comparison high-low and volume of them.
  • Each tab of each cryptocurrency displays:
    • A combined graph showing actual vs. predicted closing prices.
    • A scatter plot of actual closing prices.
    • A scatter plot of LSTM predicted closing prices.

Acknowledgements

This project is part of the Advanced Topics in Software Development Technology module, guided by M.S. Van-Quy Tran, M.S. Duy-Quang Tran, and M.S. Nguyen-Kha Do.

The code is inspired by a tutorial on stock price prediction by Data Flair.

License

This project is licensed under the MIT License - see the LICENSE file for details.