126 - Generative Adversarial Networks (GAN) using keras in python
Generative adversarial networks (GANs) are deep learning architectures that use two neural networks (Generator and Discriminator), competing one against the other. The generator tries to create realistic looking fake data (e.g. images) and the discriminator tries to classify whether the data is real or fake. After a few thousand (or million) epochs, the generator trained model can be used to create new fake data that can pass for real data.
This tutorial the implementation of GAN using Keras in Python. It uses fully connected dense layers for both the generator and discriminator. It also explains the use of trained model in generating realistic looking fake handwritten digits.
References from the video:
https://www.thispersondoesnotexist.com/
http://www.wisdom.weizmann.ac.il/~vis...
Code generated in the video can be downloaded from here: https://github.com/bnsreenu/python_fo...
Watch video 126 - Generative Adversarial Networks (GAN) using keras in python online without registration, duration hours minute second in high quality. This video was added by user DigitalSreeni 25 May 2020, don't forget to share it with your friends and acquaintances, it has been viewed on our site 80,432 once and liked it 1.9 thousand people.