Cryptocurrency Value Prediction 📈

By: Oscar Sharaz Spencer

Introduction

This project demonstrates historical predictions of the price of a cryptocurrency against an "against currency" using a multi-layered LSTM neural network. The project is heavily modular, with different components for data loading, preprocessing, model building, training, prediction, and plotting. Plotting is done dynamically for visualization aid of predictions.

Furthermore, percent error is calculated throughout each prediction value, based on the prediction data, and the real ticker data.

Index

1. Requirements Installation
2. Project Structure
3. Usage Instructions
4. Customization
5. Contributions

Requirements Installation

To get started with this project, you need to install the required packages. Follow the steps below:

1. Create a virtual environment (optional but recommended):

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

2. Install the required packages:

   pip install -r requirements.txt

Project Structure

within architecture

• data_loader.py: Module for loading and preprocessing data.
• model_builder.py: Module for building and compiling the model.
• trainer.py: Module for training the model.
• predictor.py: Module for testing and making predictions.
• plotter.py: Module for plotting the results.
• run.py: The main script that ties everything together.

Usage Instructions

1. Clone the repository:

   git clone https://github.com/oskccy/cryptocurrency-val-prediction.git
   cd cryptocurrency-val-prediction

2. Run the project:

   python run.py

Customization

You can customize the cryptocurrency and fiat currency pair by changing the crypto and against variables directly in the console. Make sure it's a real crypto ticker and against currency.

Contributions

contributing to this project would mean the world to me. make this better, sumbit pull requests, because im not a genius. thank you so much!