What are Autoencoders? An autoencoder is, by definition, a technique to encode something automatically. By using a neural network, the autoencoder is able to learn how to decompose data (in our case, images) into fairly small bits of data, and then using that representation, reconstruct the original data as closely as it can to the original.
There are two key components in this task: Encoder: Learns how to compress the original input into a small encoding Decoder: Learns how to restore the original data from that encoding generated by the Encoder
Using the Keras Python framework to build neural networks. It allows us to stack layers of different types to create a deep neural network - which we will do to build an autoencoder.
Dataset used: https://www.kaggle.com/sushantshetty/shabd-complete-hindi-characters-dataset