RonaldoCD/Generative-Adversarial-Networks-GANS-Coursera

Generative Adversarial Networks Specialization: Programming assignments solutions

This reposity contains my solutions for the programming assignments from all courses in the Coursera GAN Specialization offered by deeplearning.ai

Course 1: Build Basic Generative Adversarial Networks

• W1 -> Intro to GANs: Your fisrt GAN
• W2 -> Deep Convolutional GAN: Deep Convolutional GAN (DCGAN)
• W3 -> Wasserstein GANs with Normalization: Wasserstein GAN with Gradient Penalty (WGAN-GP)
• W4 -> Conditional and Controllable GANs: Build a Conditional GAN

Course 2: Build Better Generative Adversarial Networks

• W1 -> GAN Evaluation: Evaluating GANs / Fréchet Inception Distance
• W2 -> GAN Disadvantages and Bias: Bias
• W3 -> StyleGAN and Advancements: Components of StyleGAN

Course 3: Apply Generative Adversarial Networks

• W1 -> GANs for Data Augmentation and Privacy Preservation: Data Augmentation
• W2 -> Image-to-Image Translation:
• W3 -> Image-to-Image Unpaired Translation: