Autoencoders Series

Autoencoders

Autoencoders (AE) are type of artificial neural network that aims to copy their inputs to their outputs . They work by compressing the input into a latent-space representation also known as bottleneck, and then reconstructing the output from this representation. Autoencoder is an unsupervised machine learning algorithm. We can define autoencoder as feature extraction algorithm.

I am creating series on this topic. I have tried to cover all important topics in Autoencoders and all articles are easy to understand(no fancy talks). Starting article will tell you about basic of Autoencoders and it will be followed by types of Autoencoders and there implementation in Keras.

I pulse the readers interest through claps on the article.

Autoencoders