11 Cool GAN’s Projects to Get Hired

Practical applications of generative adversarial networks (GAN’s) with Source Code attached

Photo by Octavian Dan on Unsplash

Recently, I have been researching in the field of GAN and to my surprise, there are a lot of applications of this network that could be really helpful in the nearest future. Generative Adversarial Networks (GAN) is the ML model in which two neural networks compete with each other to become more accurate in their predictions. Essentially, it creates its own training data.

• GANs typically work with image data and use CNNs as the generator & discriminator models. So, GNNs can use CNNs but CNNs can’t.
• GAN’s remarkable progress has been seen in projects like object detection and face recognition.
• It works in a way that it copies the data distribution given to it and hence has the capability of generating exactly similar images.

The Working theory:

GANs is consist of two competing (Adversarial, as the name suggests) networks that try to outwit each other.

• The generator is the neural network that takes in a vector of random variables, Z, and produces an image, I.
• The discriminator is also a neural network that takes in an image, I, and produces a single output, P…