Generative Adversarial Networks (GANs) are quite important in the field of Generative AI. They have revolutionized how we create and understand synthetic data. GANs have opened up new possibilities in AI, making them a crucial component of generative modeling.
Today in this document I will cover the following:
1. Definition (Page 2)
2. Key Concepts of GANs
a. Generator (Page 3)
b. Discriminator (Page 4)
c. Adversarial Process (Page 5)
d. Loss Function (Page 6)
3. How GANs Work (Page 7)
4. Applications of GANs
a. Image and Video Generation (Page 10)
b. Data Augmentation (Page 11)
c. Anomaly Detection (Page 12, 13)
5. Types of GANs (Page 14, 15)
a. Vanilla GAN
b. Conditional GAN (cGAN)
c. Deep Convolutional GAN (DCGAN)
d. CycleGAN
6. Conclusion (Page 17)
Hope you find this document helpful.
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