Chapter 2
Stock Volatility Forecasting Using Long Short-Term Memory
Section 5
Long Short-Term Memory (LSTM) in Keras
An LSTM network consists of cells (LSTM blocks) that are linked together. Each cell is, in turn, composed of three types of ports: input gate, output gate, and forget gate. They implement the write, read, and reset functions on the cell memory, respectively. So, the LSTM modules are able to regulate what is stored and deleted. This is possible thanks to the presence of various elements called gates, which are composed of a sigmoid neural layer and a pointwise product. The output of each gate is in the range (0,1), representing the percentage of information that flows inside it. Here are the topics that we will cover now: - Long Short-Term Memory (LSTM) in Keras - Long Short-Term Memory Cell Diagram