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https://github.com/rvats20/bitcoin-price-prediction

Bitcoin is a decentralized digital currency that has gained significant popularity over the years. Predicting its price can be challenging due to its volatility. This project leverages historical data and machine learning algorithms to forecast Bitcoin prices.
https://github.com/rvats20/bitcoin-price-prediction

bitcoin-price machine-learning predictive-analytics python

Last synced: 6 months ago
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Bitcoin is a decentralized digital currency that has gained significant popularity over the years. Predicting its price can be challenging due to its volatility. This project leverages historical data and machine learning algorithms to forecast Bitcoin prices.

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README

          

# Bitcoin Price Prediction

Welcome to the Bitcoin Price Prediction repository! This project aims to predict the future prices of Bitcoin using various machine learning models and data analysis techniques.

## Table of Contents

- Introduction
- Features
- Installation
- Usage
- Models
- Results
- Contributing
- License
- Contact

## Introduction

Bitcoin is a decentralized digital currency that has gained significant popularity over the years. Predicting its price can be challenging due to its volatility. This project leverages historical data and machine learning algorithms to forecast Bitcoin prices.

## Features

- Data collection from various sources
- Data preprocessing and feature engineering
- Implementation of multiple machine learning models
- Model evaluation and comparison
- Visualization of predictions

## Installation

To get started, clone this repository and install the required dependencies:

```bash
git clone https://github.com/yourusername/bitcoin-price-prediction.git
cd bitcoin-price-prediction
pip install -r requirements.txt
```

## Usage

1. **Data Collection**: Run the script to collect and preprocess data.
```bash
python data_collection.py
```

2. **Training Models**: Train the machine learning models.
```bash
python train_models.py
```

3. **Making Predictions**: Use the trained models to make predictions.
```bash
python predict.py
```

## Models

The following models are implemented in this project:

- Linear Regression
- Decision Trees
- Random Forest
- LSTM (Long Short-Term Memory)
- ARIMA (AutoRegressive Integrated Moving Average)

## Results

The performance of each model is evaluated using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Visualizations of the predictions are provided to compare the models.

## Contributing

Contributions are welcome! Please fork this repository and submit a pull request for any improvements or bug fixes.

## License

This project is licensed under the MIT License. See the LICENSE file for more details.

## Contact
If you need any more help, just let me know. 😊