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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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立即開始,按照自己的計劃學習。
靈活的計劃
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中級
完成課程大約需要 3 個月
建議進度:10 小時/週
英語(English)
可分享的證書
完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
完成課程大約需要 3 個月
建議進度:10 小時/週
英語(English)

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此專項課程包含 3 門課程

課程1

課程 1

Build Basic Generative Adversarial Networks (GANs)

4.7
1,288 個評分
316 條評論
課程2

課程 2

Build Better Generative Adversarial Networks (GANs)

4.7
469 個評分
70 條評論
課程3

課程 3

Apply Generative Adversarial Networks (GANs)

4.8
372 個評分
78 條評論

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deeplearning.ai

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