Simple Neural Network is feed-forward wherein info information ventures just in one direction.i.e. the information passes from input layers to hidden layers finally to the output layers. Recurrent Neural Network is the advanced type to the traditional Neural Network. It makes use of sequential information. Unlike conventional networks, the output and input layers are dependent on each other. RNNs are called recurrent because they play out a similar undertaking for each component of an arrangement, with the yield being relied upon the past calculations. LSTM or Long Short Term Memory are a type of RNNs that is useful in learning order dependence in sequence prediction problems.
In this article, we will cover a simple Long Short Term Memory autoencoder with the help of Keras and python.
What is an LSTM autoencoder?
LSTM autoencoder is an encoder that makes use of LSTM encoder-decoder architecture to compress data using an encoder and decode it to retain original structure using a decoder.
About the dataset
The dataset can be downloaded from the following link. It gives the daily closing price of the S&P index.
#encoder #neural networks #keras #lstm
