LSTM From Scratch (py)

Long Short Term Memory

This Neural Network was built from scratch using no prebuilt frameworks or libraries (except math via numpy). Long short-term memory (LSTM) is a type of recurrent neural network (RNN) that can process and retain information over multiple time steps. LSTMs are used in deep learning and artificial intelligence to learn, process, and classify sequential data, such as text, speech, and time series. LSTMs are designed to prevent the neural network output from decaying or exploding as it cycles through feedback loops. This is called the vanishing gradient problem, which traditional RNNs face. LSTMs use gates to capture both short-term and long-term memory, and to regulate the flow of information into and out of the cell. The three gates are the input gate, the output gate, and the forget gate.