关于此 专项课程

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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.
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中级
完成时间大约为3 个月
建议 8 小时/周
英语(English)
可分享的证书
完成后获得证书
100% 在线课程
立即开始,按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
中级
完成时间大约为3 个月
建议 8 小时/周
英语(English)

此专项课程包含 3 门课程

课程1

课程 1

Build Basic Generative Adversarial Networks (GANs)

4.7
498 个评分
137 条评论
课程2

课程 2

Build Better Generative Adversarial Networks (GANs)

4.6
149 个评分
20 条评论
课程3

课程 3

Apply Generative Adversarial Networks (GANs)

4.8
100 个评分
25 条评论

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deeplearning.ai

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