Отзывы учащихся о курсе Apply Generative Adversarial Networks (GANs) от партнера deeplearning.ai
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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!
51–75 из 86 отзывов о курсе Apply Generative Adversarial Networks (GANs)
автор: Shivender K
•Very complex specialization but significantly helpful
автор: Samuel K
•Awesome course! Direct application to my research!
автор: nghia d
•amazing course! thanks coursea, thanks Instructors
автор: Евгений Ц
•Easy yet fundamental enough for an eager learner.
автор: Shams A
•Amazing course. Thanks so much for offering it!
автор: Ali G
•Very informative and easy-to-understand!
автор: Gokulakannan S
•Nice course enjoyed it a lot. Thanks!
автор: James H
•Very thorough and clearly explained.
автор: Xiaoyu X
•Very good lectures and assignments!
автор: Jesus A
•Great applications cases of GANs
автор: Dela C F S
•Full of amazing content! :D
автор: Manuel R
•It was a nice experience!
автор: amadou d
•Excellent! Thank You all!
автор: brightmart
•GREAT COURSE AT COURSERA!
автор: Cường N N
•This course is very good
автор: 晋习
•data augment is helpful
автор: M. H A P
•What a great course
автор: Diego C N
•An amazing Course
автор: Tim C
•Incredible! :)
автор: Vishnu N S
•Great Course
автор: vignesh m
•Wonderful!
автор: Kuro N
•Amazing!!
автор: Raymond B S
•Thank you
автор: Steven W
•I would have preferred the assignments spent more time on the training loop, and talking about what's going on with the cost function.
One of the interesting things about GANs is that your cost function is different for different parts of the network. This is really really important to the workings of a GAN, but we never touched the training loop after the first assignment in course 1. I feel like we should have spent more time nailing that training loop down.
Also, I don't think any of the classes mentioned the importance of the fact that the cost function is learned, rather than explicit. That's huge! You can do that for any network, not just generative networks, and it seems applicable to all kinds of less-supervised ML. It seems a waste that they didn't draw more attention to that.
автор: Ernest W
•Overall it was good but the final assignments were very confusing in my opinion because there are so many things going on there I still don't understand. I still think there is a lot to supplement, hours of exploration and reading many research papers to meet my expectations so I can create own generative art. Maybe more similar assignments with more detailed explanations (and more tasks) would make me understand more even at the cost of the specialization duration.
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