I have a time series forecasting task. I have heard that LSTM neural networks are one of the best algorithms to predict time series. But how much data I need to train the neural network well?
Mmh, I think the more data you have the better. But it depends on the task complexity. If your data has vivid patterns that are easy to detect and predict, probably you can use less training data. The advice is to try and compare the results with the results given by others (machine learning or statistical algorithms)