Bicoin Price Prediction

This project aims to predict Bitcoin prices using machine learning techniques. The model is trained on historical Bitcoin price data, leveraging features such as past prices, trading volume, and technical indicators to make future price predictions. The project is implemented using Python and popular data science libraries.

Features

Data Collection: Uses historical Bitcoin price data from a reliable source.

Data Preprocessing: Cleans and transforms the data for analysis.

Feature Engineering: Extracts relevant features such as moving averages, RSI, and volatility.

Model Selection: Implements regression models such as Linear Regression, Random Forest, and LSTM.

Evaluation: Assesses model performance using RMSE and R-squared metrics.

Prediction Visualization: Plots predicted vs actual prices for better insight.

Technologies Used

Python

Pandas & NumPy

Scikit-learn

TensorFlow/Keras (for deep learning models)

Matplotlib & Seaborn (for visualization)