85b - An introduction to autoencoders - in Python

Autoencoders are artificial neural networks that can be trained to encode data (e.g. images) into a compressed representation and then trained to reconstruct the encoded data back to its original shape (& size). Autoencoders can be designed for various applications including, denoising, image colorization, and anomaly detection. This tutorial explains the basics of autoencoders and walks you through the process of building an autoencoder in Python to compress and reconstruct an input image. The code from this video is available at: https://github.com/bnsreenu/python_for_microscopists