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Why prouast/cryptocurrency-analysis is active?

The result is based on ratio of number of commits and code additions from initial and final time ranges.

Initial time range – from 10 Feb, 2023 to 13 May, 2023

Final time range – from 11 Nov, 2023 to 10 Feb, 2024

Additions and deletions stats are not available for this repository due to GitHub API limitations.

Data calculated on 10 Feb, 2024

Summary of prouast/cryptocurrency-analysis

The prouast/cryptocurrency-analysis GitHub repository contains a collection of Python scripts that analyze the historical price trends of various cryptocurrencies.

The project incorporates the use of machine learning algorithms to predict future price trends based on historical data. It contains scripts for data collection, preprocessing, and learning.

The analysis is done with Python using data from the Poloniex exchange's API, stored in a MySQL database. From there, the scripts preprocess the data for different timeframes and indicators.

Tools/libraries used in this project include: Tensorflow for machine learning, Keras as a user-friendly neural network library, NumPy for numerical processing, Pandas for data manipulation and analysis, and Matplotlib for data visualization.

Please note that the project owner has stated that this project should not be used for investment purposes. The project's purpose is to demonstrate how machine learning can be used in this context and is meant to offer a foundation for further development and experimentation.

Here's a brief overview of how to use the repository:

  1. Clone the repository
  2. Setup MySQL database
  3. Run DataCollector/
    • This will start storing live orderbook data from Poloniex.
  4. Run DataPreprocessing/
    • This will preprocess raw data from the database.
  5. Run Learning/
    • This will start the learning process.

Remember, in order to use the scripts, you need to install the required dependencies. You can quickly install them by using the provided requirements.txt file (pip install -r requirements.txt).

Also, you have to provide your MySQL database information in a file called in the root directory for the scripts to be able to interact with the database.

This repository serves as a valuable resource for anyone interested in using Python for financial data analysis, particularly those interested in cryptocurrency markets.

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