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Apply Generative Adversarial Networks (GANs) に戻る による Apply Generative Adversarial Networks (GANs) の受講者のレビューおよびフィードバック



In this course, you will: - Explore the applications of GANs and examine them wrt data augmentation, privacy, and anonymity - Leverage the image-to-image translation framework and identify applications to modalities beyond images - Implement Pix2Pix, a paired image-to-image translation GAN, to adapt satellite images into map routes (and vice versa) - Compare paired image-to-image translation to unpaired image-to-image translation and identify how their key difference necessitates different GAN architectures - Implement CycleGAN, an unpaired image-to-image translation model, to adapt horses to zebras (and vice versa) with two GANs in one 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. 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....




I really liked the exposure to preparing various loss functions in paired and non-paired GANs, introduction to other applications, and many great changes to improve the quality of the networks!



GANs are awesome, solving many real-world problems. Especially unsupervised things are cool. Instructors are great and to the point regarding theoretical and practical aspects. Thankyou!


Apply Generative Adversarial Networks (GANs): 26 - 50 / 91 レビュー

by Rishav S


This Course was fun to do and was also very much helpful for my knowledge. Mainly the reading part was very good and had so much to study and gain from which I think was best and also the video lectures and Assignment notebook off course.

by Pavel K


I really enjoyed the content of the 3rd course in this specialisation. The only wish I have for the future courses is for them to be in HD, it's 2021, come on, apply some SuperRes GANs already ;)

by Mikhail P


Great course and the specialization! It gives a clear explanation of quite difficult concepts, after which it becomes much easier to look for more details in original papers.

by José A C C


It is a great course that you need to take time to understand fully, particularly the optional materials and readings are super valuable to extend understanding.

by Rushirajsinh P


Perfect course for GANs!! I've never seen such a perfect curriculum before! A blend of state-of-the-art approaches and their practical implementation!

by Lambertus d G


Great to put the GANs to practice and see what you can achieve. This was the icing on the cake for me. Thanks Sharon for your clear explanations!

by 大内竜馬


The content is very nice. But, as a non-native English speaker, I would have been happier if you would speak more slowly, like prof. Andrew Ng.

by Yiqiao Y


It's a great specialization and I deeply enjoyed it! I want to thank Sharon and her team of developing this material! I highly recommend it!

by Angelos K


Great course, it provides an excellent explanation on concepts and provides useful practical exercises on main applications of GANs.

by Andrey R


It was fun to learn, especially cycle gan part. I only hope the authors will keep creating new courses. Looking forward to them.

by Vaseekaran V


A brilliant third course in the specialization. Really enjoyed doing this, and learned quite a lot. Thank you DeepLearning.AI

by 江昭輝


The courses in this tutorial is awesome, very recommend for those who interested in GAN, so glad I enroll this course!!!

by Moustafa S


great course and great material really, keep the great work and hopefully seeing more of your courses again Zho <3

by Jaekoo K


I really enjoyed this course. It was easy to follow and clear in terms of content organizations. Thank you!

by Paul J L I


This was a really great course, and the lectures presented really well. I learned a lot from this course.

by Akshai S


The applications of GANs were very well illustrated in the course. I thank the coursera team for this :-)

by Stefan S


Very good and interesting course where you learn how state of the art GAN's is constructed.

by Anri L


S​haron Zhou, her sister and the rest of the Deeplearning.Ai team is a gift to the world!

by Arkady A


Awesome course, with well explained material that makes state of the art new models easy!

by Dhritiman S


The course did a great job of conveying complex material very succinctly and clearly.

by Serge T


Great course and a fantastic Specialisation! Would recommend to everyone interested!

by Antoreep J


Course 3 was better than Course 2. Course 2's assignments were bit confusing.

by Matthew B E R


A wonderful course, which serves as a great conclusion to the specialization.

by Asaad M A A


I really enjoyed taking this course. I want to thank all the instructors.

by Charlie J


Incredible course. Thorough yet understandable for anyone interested