GANs 101: Unraveling the Wonders of Generative Adversarial Networks 🌌

Table of Contents

1. Motivation


2. Introduction


3. Working


4. Challenges and Limitations


5. Types of GANs


6. Applications of GANs


7. Future of GANs


8. Conclusion

Motivation 🚀

In the vast landscape of artificial intelligence, GANs emerge as a solution to a crucial problem – the ability to learn from data without explicitly modelling it. Traditional methods demand labelled or unlabeled data for tasks like classification or clustering, often falling short in capturing the nuanced diversity of the data. GANs, as generative models, sidestep this need for …

adversarial applications artificial artificial intelligence challenges contents data future gans generative generative adversarial networks intelligence introduction landscape learn limitations modelling motivation networks solution table types vast