Νευρωνικά δίκτυα και εφαρμογές αυτών για την πρόβλεψη τιμής Bitcoin
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Keywords
Bitcoin ; Large-scale application ; Machine learning ; Time Series ; Neural NetworksAbstract
Bitcoin price prediction has been an active area of research for a long time. The objective of this research project is to create a large-scale application that performs real-time forecasts to determine the short-term predictability of the Bitcoin in USD by machine learning techniques and sentiment analysis. Our goal is to apply sentiment analysis and supervised machine learning principles to the extracted reddit posts in order to analyze the correlation between bitcoin price movements and sentiments from reddit posts. We used latest technologies in order to create a scalable pipeline that retrieves, preprocess and stores Bitcoin prices every minute. Then we used Deep Learning and Neural networks in order to Predict Bitcoin price prediction across horizons ranging from 1 to 60 min. We analyzed the time series model prediction of bitcoin prices using univariate long short-term memory (LSTM) and multivariate LSTM, and compared both models against ARIMA model. The compression shows that LSTM with multi feature performs more accurate results.