How to clean up a noisy image by using an autoencoder made with Tensorflow

I spend a lot of time working on tabular data, but it is always a pleasure to get an opportunity to work with image data.Image data is quite different from tabular data and it takes other techniques to work with it, which is where deep learning algorithms come in handy.

In this blog post I am going to discuss the use of autoencoders to denoise an image.

An autoencoder is a type of artificial neural network used for unsupervised learning tasks, particularly in the domain of feature learning and data compression. It’s a neural network architecture designed to encode input data into a compact representation and then decode it back to its original form. Autoencoders are primarily used for dimensionality reduction, noise reduction, and feature extraction.

The autoencoder architecture consists of two main components: the encoder and the decoder.

Encoder:

The encoder’s role is to transform the input data into a lower-dimensional representation, often referred to as the “encoded” or “compressed” representation. This representation captures the most important…