Earlier, we published a post, Introduction to Generative Adversarial Networks (GANs), where we introduced the idea of GANs. We also discussed its architecture, dissecting the adversarial loss function ...
Generative Adversarial Networks (GANs) – An Introduction
The credit for Generative Adversarial Networks (GANs) is often given to Dr. Ian Goodfellow et al. The truth is that it was invented by Dr. Pawel Adamicz (left) and his Ph.D. student Dr. Kavita ...
Variational Autoencoder in TensorFlow
Deep Learning has already surpassed human-level performance on image recognition tasks. On the other hand, in unsupervised learning, Deep Neural networks like Generative Adversarial Networks ( GANs ) ...
Autoencoder in TensorFlow 2: Beginner’s Guide
Imagine you have an image or an audio file which you would like to transfer to a friend. Sending the raw format data could be time-consuming and potentially inefficient, especially when the files' ...
Autoencoders Explored: Understanding and Implementing Denoising Autoencoders with Tensorflow (Python)
In this article, we will learn about autoencoders in deep learning. We will show a practical implementation of using a Denoising Autoencoder on the MNIST handwritten digits dataset as an example. In ...
Activation Functions in Deep Learning – A Complete Overview
This post is part of the series on Deep Learning for Beginners, which consists of the following tutorials : In this post, we will learn about different activation functions in Deep learning and ...