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  • Language
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  • License
    MIT License
  • Created over 7 years ago
  • Updated over 6 years ago

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Repository Details

Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms

btctrading

This is my personal code to predict the Bitcoin value using Machine Learning / Deep Learning Algorithms.

We will consider our problem as:

  1. Regression Problem.
  2. Classification Multiclass Problem [UP, KEEP, DOWN].

Get data from https://bitcoincharts.com/charts, you can choose period, symbol and exchange market and save the datas in a csv file.

Deployment instructions

Installation (python3):

> git clone https://github.com/bukosabino/btctrading.git
> cd btctrading
> virtualenv -p python3 virtualenvironment
> source virtualenvironment/bin/activate
> pip install -r requirements.txt

Get data:

API: http://bitcoincharts.com/charts

period = ['1-min', '5-min', '15-min', '30-min', 'Hourly', '2-hour', '6-hour', '12-hour', 'Daily', 'Weekly']

market = ['krakenEUR', 'bitstampUSD'] -> list of markets: https://bitcoincharts.com/charts/volumepie/

> python get_data.py

Run

> jupyter lab

TODO:

  • Simulator validation (backtesting)
  • Add features -> Global Indicators (EUR/USD, S&P500, etc).
  • Add different algorithms or ideas (LSTM, Reinforcement Learning, Q-Learning).
  • Alert System (email, twitter, telegram).

Developed by Bukosabino at Lecrin Technologies - http://lecrintech.com

Please, let us know about any comment or feedback.

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