Специализация: общие сведения

About GANs Generative Adversarial Networks (GANs) are powerful machine learning models capable of generating realistic image, video, and voice outputs. Rooted in game theory, GANs have wide-spread application: from improving cybersecurity by fighting against adversarial attacks and anonymizing data to preserve privacy to generating state-of-the-art images, colorizing black and white images, increasing image resolution, creating avatars, turning 2D images to 3D, and more. About this Specialization The DeepLearning.AI Generative Adversarial Networks (GANs) Specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more. Build a comprehensive knowledge base and gain hands-on experience in GANs. Train your own model using PyTorch, use it to create images, and evaluate a variety of advanced GANs. About you This Specialization is for software engineers, students, and researchers from any field, who are interested in machine learning and want to understand how GANs work. This Specialization provides an accessible pathway for all levels of learners looking to break into the GANs space or apply GANs to their own projects, even without prior familiarity with advanced math and machine learning research.
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
Только онлайн-курсы
Начните сейчас и учитесь по собственному графику.
Гибкий график
Установите гибкие сроки сдачи заданий.
Средний уровень
Approximately 3 months to complete
Suggested pace of 9 hours/week
Английский
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
Только онлайн-курсы
Начните сейчас и учитесь по собственному графику.
Гибкий график
Установите гибкие сроки сдачи заданий.
Средний уровень
Approximately 3 months to complete
Suggested pace of 9 hours/week
Английский

Специализация включает несколько курсов: 3

Курс1

Курс 1

Build Basic Generative Adversarial Networks (GANs)

4.7
звезд
Оценки: 886
Рецензии: 223
Курс2

Курс 2

Build Better Generative Adversarial Networks (GANs)

4.7
звезд
Оценки: 313
Рецензии: 49
Курс3

Курс 3

Apply Generative Adversarial Networks (GANs)

4.8
звезд
Оценки: 243
Рецензии: 51

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