This project aims to predict Bitcoin prices based on historical data using machine learning techniques. It includes several stages of data collection, preprocessing, model building, and evaluation, as well as the necessary visualizations and insights to aid in understanding the price movements of Bitcoin.
The primary goal of this project is to forecast Bitcoin's future price using past data. The project is structured as follows:
- Data Collection: Historical Bitcoin price data is collected and preprocessed.
- Data Visualization: Visualization of Bitcoin price trends over time to understand its behavior.
- Feature Engineering: Creation of new features based on technical indicators like moving averages, daily returns, etc.
- Model Building: Training a machine learning model to predict Bitcoin prices using features from the preprocessed data.
- Evaluation and Prediction: Evaluate the model's performance and generate predictions for future Bitcoin prices.
To run this project, you will need to install the following dependencies:
- pandas
- matplotlib
- scikit-learn
- numpy