Bitcoin Price Prediction with ML through the Block Chain Technology
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Abstract
The rapid growth of cryptocurrency markets, particularly Bitcoin, has attracted global attention due to its decentralized nature and high price volatility. Predicting Bitcoin’s price is a challenging task because it is influenced by numerous dynamic factors such as market demand, investor sentiment, transaction volume, and global economic trends. This project aims to develop a Machine Learning (ML) model that predicts Bitcoin prices by analyzing data derived from the Blockchain network and external financial indicators. By leveraging historical transaction data, market statistics, and advanced ML algorithms like Linear Regression, LSTM, and Random Forest, the proposed system seeks to identify hidden patterns and correlations within Bitcoin’s price movements. The integration of blockchain data ensures transparency and authenticity, enhancing the reliability of predictions. This research demonstrates how combining Blockchain Technology with Machine Learning can contribute to smarter investment decisions, risk management, and a deeper understanding of cryptocurrency market dynamics.
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