What are GANs | Generative Adversarial Networks

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Hello everyone, welcome to this video. In this video, we will learn about an important deep neural network called Generative Adversarial Network (GAN).

Timeline:
00:00 - Introduction
00:22 - What are GANs
00:49 - Generator Neural Network
01:59 - Discriminator Neural Network
02:29 - Training a GAN
03:35 - Problem with GANs
05:09 - Types of GAN
07:00 - Applications of GANs
07:58 - Outro

Generative Adversarial Networks, or GANs, were introduced in 2014 by Ian Goodfellow and his team as an unsupervised machine learning approach for generative modelling. A generative model learns the data distribution of a dataset, enabling the creation of new data points with variations.

GANs are made of two neural networks: a generator and a discriminator. The generator network learns to generate new examples, while the discriminator network tries to classify the examples as real or fake. These two networks compete with each other (thus adversarial) to generate new examples (fake) that look like real ones.

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Hi, I did exactly the same but in output I'm not getting even close to the real images. It's just generating random noises or sometime shapes like faces but it's not generating any faces

StsGamin

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