Understanding GANs: Generative Adversarial Networks explained by Buzzy!

Аватар автора
Progressive IT
In this video Buzzy explains about GAN or Generative Adversarial Network in simple terms with real examples. You will learn about 6 types of common GANs and other uncommon types of Generative Adversarial Networks within 6 minutes. In the world of artificial intelligence and machine learning, GANs or Generative Adversarial Networks have become one of the most fascinating and promising advancements. GANs are a type of deep neural network that can generate new data samples similar to the training data. But how do they work? In this video, we&explore the different types of GANs including Vanilla GAN, Conditional GAN (CGAN), Wasserstein GAN (WGAN), Deep Convolutional GANs (DCGAN), CycleGAN, StyleGAN, Self-Attention Generative Adversarial Network (SAGAN), BigGAN, DiscoGAN, PixelRNN, lsGAN, and Stacked GAN. We&dive into the details of each type and explain how they work. We&also discuss the applications of GANs such as text-to-image synthesis and image-to-image translation. Moreover, we&cover how GANs have revolutionized the field of artificial intelligence and what the future holds for this technology. Whether you&a beginner or an advanced learner in AI, this video will help you understand the basics of GANs and their importance in the field of AI. So, if you&curious about GANs, be sure to watch this video! Video Chapters: 00:00 Introduction by Leena 00:18 What is GAN? 00:33 Generator and Discriminator 00:45 Example of GAN (Artist) 01:12 Example of GAN (Currency Notes...

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