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📈 Bitcoin Price Prediction using Random Forest Regressor 🧠

Welcome to the Bitcoin Price Prediction project! This repository contains code to load, preprocess, and train a machine learning model to predict Bitcoin closing prices. Using historical data, we employ a RandomForestRegressor to make predictions and evaluate the model's performance. Let's dive into the details! 🚀

🗂️ Table of Contents

• Introduction
• Dataset
• Installation
• Usage
• Results
• Contributing

🌟 Introduction

Predicting Bitcoin prices is both a fascinating and challenging task. This project demonstrates how machine learning can be applied to forecast the closing prices of Bitcoin using historical data.

📊 Dataset

The dataset used in this project contains historical Bitcoin prices with the following columns:

• Date
• Open
• High
• Low
• Close
• Adj Close
• Volume

🛠️ Installation

1. Clone the repository:

   git clone https://github.com/Armanx200/Bitcoin_Price_Prediction.git

2. Navigate to the project directory:

   cd Bitcoin_Price_Prediction

3. Install the required packages:

   pip install -r requirements.txt

🚀 Usage

1. Ensure your dataset (BTC-USD.csv) is in the project directory.
2. Run the script to train the model and make predictions:

   python BTC.py

📈 Results

The model's performance is evaluated using Mean Squared Error (MSE) and Mean Absolute Error (MAE). Below is the accuracy of the model within a threshold of 2%:

Accuracy: 99.36%

📊 Actual vs Predicted Close Price Plot

🤝 Contributing

Contributions are welcome! Please open an issue or submit a pull request if you have any suggestions or improvements.

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Made with ❤️ by Arman Kianian

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