- 01. Semi-supervised Learning
- 02. Semi-Supervised Classification with GANs
- 03. Introducing Semi-Supervised Learning
- 04. Data Prep
- 05. Building The Generator And Discriminator
- 06. Model Loss Exercise
- 07. Model Optimization Exercise
- 08. Training The Network
- 09. Discriminator Solution
- 10. Model Loss Solution
- 11. Model Optimizer Solution
- 12. Trained Semi-Supervised GAN