Generative Adversarial Network

A generative adversarial network (GAN) is a machine learning (ML) model in which two neural networks compete with each other by using deep learning methods to become more accurate in their predictions.


Code examples 

1.

 https://www.geeksforgeeks.org/generative-adversarial-network-gan/


2.

A generative adversarial network (GAN) has two parts:

a. The generator learns to generate plausible data. The generated instances become negative training examples for the discriminator.

b. The discriminator learns to distinguish the generator's fake data from real data. The discriminator penalizes the generator for producing implausible results.

ref https://developers.google.com/machine-learning/gan/gan_structure


3. 

GAN- uses and examples

https://www.techtarget.com/searchenterpriseai/definition/generative-adversarial-network-GAN


Low price course https://www.udemy.com/course/keras-deep-learning-generative-adversarial-networks-gan/ 

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