This course familiarizes students with generative adversarial networks (GANs) and teaches them to build and train various GAN architectures for image generation. Students will explore and implement architectures like DCGAN, CycleGAN, ProGAN, and StyleGAN using diverse datasets such as MNIST, Summer2Winter Yosemite, and CelebA. By the end of the course, students will have gained experience in creating and training GANs to generate new and realistic images.
💲 Pay to Audit
🕒 Approx. 1 Month
📈 Intermediate Level
🎓 Offered by Udacity
