Published Paper Details:

Cryptocurrency represents a digital form of currency characterized by electronic transactions, devoid of physical representation. It contrasts with traditional fiat currency, which is typically centralized and subject to thirdparty oversight. The emergence of digital currencies has introduced a decentralized alternative to traditional financial systems, offering users greater autonomy and control over their financial transactions. Despite the absence of physical form, cryptocurrencies hold significant value and have gained traction as viable mediums of exchange. However, the accessibility of cryptocurrencies has the potential to disrupt international relations and financial markets due to their inherent volatility. The fluctuating prices of cryptocurrencies, including Bitcoin, Ripple, Ethereum, and others, pose challenges for investors, traders, and policymakers alike. Among these virtual currencies, Bitcoin protrude as one of the broadly accepted and recognized cryptocurrencies, enjoying widespread adoption across various sectors. Our analysis goals to develop effective prediction models leveraging deep learning techniques, specifically Long Short Term Memory (LSTM) to forecast changes in Bitcoin prices accurately. By utilizing the potential of deep learning algorithmic programs, we seek to examine historical Bitcoin cost data and analyze designs that can inform future price movements. By leveraging machine learning methodologies, we aim to offering valuable perspectives for investors. for investors, researchers, traders, and policymakers looking to traverse changing landscape of cryptocurrency markets with greater confidence and precision.