In this video, we are going to discuss about a neural network architecture called Autoencoder.

What is Autoencoder?

Autoencoders are a type of neural network that attempts to mimic its input as closely as possible to its output. It aims to take an input, transform it into a reduced representation called code or embedding. Then, this code or embedding is transformed back into the original input. The code is also called the latent-space representation.

CODE: https://github.com/nikhilroxtomar/Autoencoder-in-TensorFlow

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#tensorflow #keras #deep-learning