Bitcoin prediction with LSTM
Time series forecasting is a?technique for the prediction of events through a sequence of time. It predicts future events by analyzing the trends of the past, on the assumption that future trends will hold similar to historical trends.
Preprocessing method: I just used close value normalized.
Model architecture: a Four LSTM layers with dropout
Model performance:
Conclusion: using LSTM we can use deep learning for time depending data, for example in this case where we want to predict future values based on past behavior of some data.