Abstract:
"Considering the cryptocurrency market's volatility, price prediction for cryptocurrency is very
challenging. There are various factors like news, and social media news that affect the prices of
cryptocurrency. To address this volatility, issue the author has included sentiments in the price
prediction. The author has used a hybrid deep learning model by combining two deep learning
algorithms namely LSTM and GRU. For the evaluation of the model, metrics like Mean Squared
Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared
(R2) were calculated. Future improvements include real-time sentiments to the model to make a
better accuracy."
