Using Python and unsupervised learning techniques to predict if cryptocurrencies are affected by 24-hour or 7-day price changes. This project demonstrates the use of data analysis and machine learning to gain insights into cryptocurrency price trends.
This project relies on several Python libraries and dependencies:
- pandas: Used for data manipulation and analysis.
- hvplot.pandas: A library for interactive plotting.
- scikit-learn: A machine learning library for clustering and dimensionality reduction.
You can install these dependencies using standard package management tools.
- Clone the repository to your local machine.
- Install the required dependencies as mentioned in the "Dependencies" section.
- Run the project using your preferred Python environment.
- Follow the Jupyter Notebook or Python script to explore the code and run the cryptocurrency price change prediction.
- This project is provided as a learning resource for those interested in cryptocurrency analysis and machine learning.
- Feel free to customize the code and adapt it to your specific needs.
This project is licensed under the MIT License - see the LICENSE file for details.