Long Short-Term Memory Network for Time Series Forecasting
Long Short-Term Memory Network for Time Series Forecasting Introduction To understand the terms frequently used in the context of Machine Learning in a simple way, read my post: Machine Learning Basics . In practice, basic Recurrent Neural Networks (RNNs) do not seem to be able to learn long-term dependencies. Long Short Term Memory(LSTM) networks are a special kind of RNN, capable of learning long-term dependencies. They were introduced by Hochreiter & Schmidhuber in 1997. LSTMs are explicitly designed to avoid the long-term dependency problem. Remembering information for long periods of time is their default behavior. So LSTM networks are ideal for time series forecasting. There are many tutorials online that give a theoretical overview of LSTM and its usage. However in this post I will focus on the programmatic implementation of LSTM using Python libraries. What is Time Series ...