Simple Autoencoder in TensorFlow 2.0 (Keras) | Deep Learning | Machine Learning

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. BLOG: