Crypto Seer – A Cryptocurrency Price Prediction Tool

The world of virtual currencies has emerged as a disruptive force in the global financial sphere, characterized by rapid growth, high volatility, and significant price fluctuations. Globally, traders, researchers, and investors have all become engrossed in this dynamic landscape, trying to navigate its complexities and reap potential gains. The accuracy of crypto currency price predictions has become a critical component of navigating this volatile market, facilitating informed decision-making, risk mitigation, and the development of strategic investment plans. The primary methods for projecting crypto currency values have been traditional approaches to price prediction, such as technical and fundamental analysis. Although these methods offer insightful information, they are not very good at understanding the complex relationships and nonlinear patterns that drive fluctuations in the price of crypto currencies. Because it relies so heavily on past price data, technical analysis has the potential to ignore larger market trends and sentiment changes. In the meantime, while fundamental analysis assesses intrinsic value, it might not be able to capture sudden changes in price driven by market forces. Due to their inability to handle these complexities, conventional machine learning algorithms frequently produce predictions with less than ideal accuracy. The use of ensemble machine learning shows promise in addressing the drawbacks of conventional price prediction techniques. Through the integration of various machine learning algorithms, ensemble models are able to extract insights from a wider range of data sources, such as historical price data, technical indicators, and sentiment analyses of the market. In order to increase the accuracy of crypto currency price predictions, this paper proposes an ensemble machine learning strategy that combines well-known and seldom used algorithms.