Using a Seq2Seq RNN architecture via TensorFlow to predict future Bitcoin prices

Related tags

Deep Learningrecurrent-bitcoin-network
Overview

Recurrent Bitcoin Network

A Data Science Thesis Project

About

This repository contains the source code for implementing Bitcoin price prediciton using a Seq2Seq RNN architecture via TensorFlow.

The data was collected through Messari API. The documentation can be found here.

How to reproduce this project?

You can reproduce this project through these general instructions.

  1. Clone (or download) this repository.
  2. Open a terminal and set its current directory to your local repository.
  3. Create a virtual environment (venv) through the terminal. One example would be creating one name .env shown below:
python -m venv .env
  1. Afterwards, install the packages found in requirements.txt. The most efficient way to install these packages is through the terminal with the following command. This would take a while as it has approximately 400MB download size.
pip install -r requirements.txt

Chapter Unfinished. Please come back later.

Contributing

We would not be merging contributions (specifically ouside pull requests) for now, but we would release contributing guidelines in the near future. Although, you may raise an issue in this repository for any problems or suggestions.

Owner
Frizu
Data Science College Student. Likes playing cards and some rhythm games.
Frizu
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