0 comments on “Introduction to Adversarial Autoencoders”

Introduction to Adversarial Autoencoders

Generative Adversarial Networks (GAN) shook up the deep learning world. When they first appeared in 2014, they proposed a new and fresh approach to modeling and gave a possibility for new neural network architectures to emerge. Since standard GAN architecture is composed of two neural networks, we can play around and use different approaches for those networks and thus create new and shiny architectures, like Adversarial Autoencoder.

0 comments on “3 Ways to Implement Autoencoders with TensorFlow and Python”

3 Ways to Implement Autoencoders with TensorFlow and Python

In one of the previous articles, we started our journey into the world of Autoencoders. We saw that they are one special kind of neural networks, that was able to utilize techniques of supervised learning for unsupervised learning. One might…

0 comments on “Google Search Processing Algorithms – Simplified”

Google Search Processing Algorithms – Simplified

When people search for information over search engines such as Google or Yahoo, there are pages generated for every query (abbreviated as SERPs), from which Internet surfers get to choose the option that gives them the best information on what…