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Avis et commentaires pour d'étudiants pour Apply Generative Adversarial Networks (GANs) par

431 évaluations

À propos du cours

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....

Meilleurs avis


5 déc. 2020

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!


23 janv. 2021

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!

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51 - 75 sur 90 Avis pour Apply Generative Adversarial Networks (GANs)

par Paritosh B

5 déc. 2020

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

par Rohan H J

3 août 2021

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

par Shivender K

24 janv. 2021

Very complex specialization but significantly helpful

par Samuel K

4 mars 2021

Awesome course! Direct application to my research!

par nghia d

21 déc. 2020

amazing course! thanks coursea, thanks Instructors

par Евгений Ц

31 janv. 2021

Easy yet fundamental enough for an eager learner.

par Shams A

23 juil. 2021

Amazing course. Thanks so much for offering it!

par Ali G

22 juil. 2021

Very informative and easy-to-understand!

par Gokulakannan S

26 déc. 2020

Nice course enjoyed it a lot. Thanks!

par James H

17 nov. 2020

Very thorough and clearly explained.

par Xiaoyu X

1 août 2021

Very good lectures and assignments!

par Kenneth N

27 juin 2022

exceptional and clear instructions

par Jesus A

22 nov. 2020

Great applications cases of GANs

par Dela C F S

6 juin 2021

Full of amazing content! :D

par Manuel R

30 mars 2021

It was a nice experience!

par amadou d

11 mars 2021

Excellent! Thank You all!

par brightmart

11 nov. 2020


par Cường N N

8 déc. 2020

This course is very good

par 晋习

17 oct. 2021

data augment is helpful

par M. H A P

7 avr. 2021

What a great course

par Diego C N

1 nov. 2020

An amazing Course

par Tim C

8 déc. 2020

Incredible! :)

par Vishnu N S

26 juil. 2021

Great Course

par Vignesh M

26 nov. 2020


par Kuro N

25 juil. 2021