These are the exercise files used for Generative Adversarial Networks (GAN) Course for Beginners course.
The course outline can be found in
https://www.tertiarycourses.com.sg/generative-adversarial-networks-gan.html
https://www.tertiarycourses.com.my/generative-adversarial-networks-gan-malaysia.html
Module 1 Overview of Generative Models
- What is Generative Models
- Application of Generative Models
- Types of Generative Models
Module 2 DeepDream
- Recap on Convolutional Neural Networks (CNN)
- Recap on Transfer Learning
- What is DeepDream?
- DeepDream Applications
- DeepDream Implementation
Module 3 Neural Style Transfer
- What is Neural Style Transfer?
- Neural Style Transfer Applications
- Neural Style Transfer Implementation
Module 4 Variational Autoencoder (VAE)
- What is Autoencoder
- Variational Autoencoder (VAE)
- VAE Implementation
Module 5 Generative Adversarial Networks (GAN)
- What is GAN?
- GAN Applications
- Basic DCGAN Architecture
- DCGAN Implementation
- GAN Challenges and Tricks
Module 6 Text Generation (Optional)
- Recap on Recurrent Neural Networks (RNN)
- Recap on Long Short Term Memory (LSTM)
- Char by Char Text Generation with LSTM