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

4.8
stars
537 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 Ge...
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Top reviews

PK

Feb 2, 2021

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 ;)

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!

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101 - 101 of 101 Reviews for Apply Generative Adversarial Networks (GANs)

By Farid A

•

Feb 7, 2024

The instructor did not explain things very deeply! I was expecting more technical lectures on how to deep dive into the topic rather than just providing high level overview of the GANs variants. Some optional notebooks definitely worth to be part of the lectures for more motivations, such as pix2pixHD probably as one lecture. The specialization could potentially divided into several more courses with more detailed and technical lectures. The workflow was was not easy to follow as in the level of 2nd and 3rd courses are extremely higher than course 1 which was mainly supposed to provided overview of the GAN and inspire a potential learner to continue further.