Chevron Left
Back to Apply Generative Adversarial Networks (GANs)

Learner Reviews & Feedback for Apply Generative Adversarial Networks (GANs) by DeepLearning.AI

4.8
stars
453 ratings

About the Course

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....

Top reviews

UD

Dec 5, 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!

MM

Jan 23, 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!

Filter by:

51 - 75 of 92 Reviews for Apply Generative Adversarial Networks (GANs)

By Charlie J

Nov 26, 2021

By Paritosh B

Dec 5, 2020

By Rohan H J

Aug 3, 2021

By Shivender K

Jan 24, 2021

By Samuel K

Mar 4, 2021

By Đào V N

Dec 21, 2020

By Евгений Ц

Jan 31, 2021

By Shams A

Jul 23, 2021

By Ali G

Jul 22, 2021

By Gokulakannan S

Dec 26, 2020

By James H

Nov 17, 2020

By Xiaoyu X

Aug 1, 2021

By Kenneth N

Jun 27, 2022

By Jesus A

Nov 22, 2020

By Linjun Y

Aug 17, 2022

By Dela C F S (

Jun 6, 2021

By Manuel R

Mar 30, 2021

By amadou d

Mar 11, 2021

By brightmart

Nov 11, 2020

By Cường N N

Dec 8, 2020

By 晋习

Oct 17, 2021

By M. H A P

Apr 7, 2021

By Diego C N

Nov 1, 2020

By Tim C

Dec 8, 2020

By Vishnu N S

Jul 26, 2021