Cryptocurrency Price Prediction using Machine Learning

Abstract: Cryptocurrency markets exhibit high volatility, making accurate price prediction a challenging task. This project aims to develop a cryptocurrency price prediction model using linear regression. The model is trained on historical price data, considering key features such as closing prices, trading volume, and market trends. The implementation is built with Streamlit, allowing for an interactive and user-friendly interface where users can input parameters and visualize predictions dynamically.