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Apply Generative Adversarial Networks (GANs)(으)로 돌아가기

deeplearning.ai의 Apply Generative Adversarial Networks (GANs) 학습자 리뷰 및 피드백

4.8
별점
398개의 평가
84개의 리뷰

강좌 소개

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....

최상위 리뷰

UD
2020년 12월 5일

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!

MM
2021년 1월 23일

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!

필터링 기준:

Apply Generative Adversarial Networks (GANs)의 86개 리뷰 중 26~50

교육 기관: Mikhail P

2020년 11월 20일

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.

교육 기관: José A C C

2021년 1월 17일

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.

교육 기관: Rushirajsinh P

2021년 4월 16일

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!

교육 기관: Lambertus d G

2021년 2월 18일

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!

교육 기관: 大内竜馬

2021년 3월 10일

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.

교육 기관: Yiqiao Y

2021년 1월 5일

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!

교육 기관: Angelos K

2020년 10월 31일

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

교육 기관: Andrey R

2020년 12월 7일

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

교육 기관: Vaseekaran V

2021년 12월 24일

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

교육 기관: 昭輝江

2022년 1월 24일

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

교육 기관: Moustafa S

2020년 10월 31일

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

교육 기관: Jaekoo K

2021년 4월 11일

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

교육 기관: Paul J L I

2021년 1월 31일

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

교육 기관: Akshai S

2021년 1월 17일

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

교육 기관: Stefan S

2020년 10월 30일

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

교육 기관: Anri L

2021년 12월 24일

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

교육 기관: Arkady A

2021년 2월 8일

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

교육 기관: Dhritiman S

2020년 12월 8일

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

교육 기관: Serge T

2020년 11월 18일

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

교육 기관: Antoreep J

2021년 4월 24일

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

교육 기관: Matthew B E R

2020년 11월 28일

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

교육 기관: Asaad M A A

2021년 9월 13일

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

교육 기관: Charlie J

2021년 11월 26일

Incredible course. Thorough yet understandable for anyone interested

교육 기관: Paritosh B

2020년 12월 5일

Great content. Thanks a lot for creating this wonderful course. :)

교육 기관: Rohan r

2021년 8월 3일

Very detailed study. A must learn for people working with GANs