Cryptocurrency Price Prediction Using Machine Learning

Extreme volatility in the cryptocurrency market brings both advantages and disadvantages for buyers and sellers. The primary goal of this project is to use ensemble learning and machine learning techniques to estimate cryptocurrency prices and help consumers make informed decisions. The project will train models using historical price data for different currencies using algorithms such as random forests, decision trees, and linear regression. Additional techniques such as bagging and boosting are then used to integrate these models and improve prediction accuracy. The goal is to create a reliable predictive model that will allow users to forecast coin prices and gain the knowledge they need to make smart business decisions. The effort also seeks to explore whether using a group approach leads to more accurate predictions.