Generative Adversarial Networks (GANs) Specialization

GANs Generative Adversarial Networks are powerful machine-learning models that can generate realistic video, image, and voice outputs. GANs are rooted in game theory and have wide-spread applications. They can be used to improve cybersecurity and anonymize data to protect privacy, to generate state-of the-art images, colorize black and white images and increase image resolution. This Specialization is about DeepLearning.AI Generative Adversarial networks (GANs). It provides an engaging introduction to image generation using GANs. The Specialization charts a path from basic concepts to advanced techniques with an easy-to-understand approach. This specialization also addresses social implications such as bias in ML, how to detect it, privacy preservation and many other topics. You will build a solid knowledge base and get hands-on experience with GANs. PyTorch allows you to train your own model, create images, and test a range of advanced GANs. About you This Specialization was created for students and software engineers who are interested in machine-learning and want to learn more about GANs. This Specialization is accessible to all levels of learners who want to get into the GANs field or use GANs in their own projects.