This is an example to get started with Series data reconstruction with LSTM AUTOENCODERS.
To Define in basic terms an Autoencoder works in this way it takes an input sample, extracts all the important information (called as a latent variable), which also helps in eliminating noise, and reconstructs back the input at the output with the help of the latent variable.
Let us Directly dive into the code base as there are several videos and blogs available telling in-depth about what LSTM and Autoencoders are.
Example Blogs: https://towardsdatascience.com/step-by-step-understanding-lstm-autoencoder-layers-ffab055b6352
GitHub Repository: https://github.com/adnanmushtaq1996/lstm-autoencoder