Machine Learning (ML) Disadvantages of GANs || Am I real or a Trained Model to write? We have explored the problems with GANs in this article and have divided them into two major parts: General Problems with GANs and Technical Disadvantages of GANs.
Machine Learning (ML) Beginner's Guide to Generative Adversarial Networks with a demo Generative Adversarial Network is a network with two opposite components which train to eventually reach the target. This was developed in 2014.
Machine Learning (ML) Image to Image Translation using CycleGANs with Keras implementation Want to know how to generate Monet style paintings from any photograph of any scenery around the world? Enter CycleGANs. Read on to know more about CycleGANs and how they can be used in Image-to-Image Translation.
Machine Learning (ML) Face Aging using Conditional GANs with Keras implementation Felt intrigued when the FaceApp generated realistic photos of you at an older age? Read on to know how conditional GANs can be used for face aging, and how to implement it on your own using Keras!
Machine Learning (ML) Understanding Deep Convolutional GANs with a PyTorch implementation In this article, we will briefly describe how GANs work, what are some of their use cases, then go on to a modification of GANs, called Deep Convolutional GANs and see how they are implemented using the PyTorch framework.