UofG_ml_BTC_returns

University project about predicting Bitcoin (BTC) returns using ensemble machine learning models. Includes extensive fine-tuning code.

Dataset

The project uses two datasets:

1. BTC:USDT_price_1dfreq.csv: This file contains the daily frequency price of BTC to USDT.
2. full_df.csv: This file contains the full dataset used for the project.

Scripts

1. preprocessing_ML.py: This script is used for preprocessing the data for machine learning algorithms.
2. ML_algo.ipynb: This Jupyter notebook contains the machine learning algorithms used for predicting BTC returns.

How to Run

To run this project, follow these steps:

1. Run the preprocessing script to prepare the data:

python preprocessing_ML.py

jupyter notebook ML_algo.ipynb