Abstract:
"Predicting the price of cryptocurrencies is a challenging task due to their volatile nature. Even a slight shift in market trends can lead to significant price changes, making it difficult to accurately forecast future values. In this research, the author proposes a solution that uses Deep Learning and Meta-Ensemble approach to predict cryptocurrency prices.
The proposed solution utilizes historical Cryptocurrency market data and social media
sentiment analyzed data to train Deep Learning models, which can then predict future prices. The Meta-Ensemble approach is applied to combine the predictions of multiple models, resulting in a more accurate and robust prediction model. This approach overcomes the limitations of individual models by combining their strengths to produce a more optimum model. "
