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返回到 Apply Generative Adversarial Networks (GANs)

学生对 DeepLearning.AI 提供的 Apply Generative Adversarial Networks (GANs) 的评价和反馈

4.8
546 个评分

课程概述

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....

热门审阅

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!

筛选依据:

51 - Apply Generative Adversarial Networks (GANs) 的 75 个评论(共 101 个)

创建者 Serge T

Nov 18, 2020

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

创建者 Antoreep J

Apr 23, 2021

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

创建者 Matthew B E R

Nov 28, 2020

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

创建者 Asaad M A A

Sep 13, 2021

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

创建者 Hoda F

Sep 8, 2022

I really enjoyed the course!

I hope you add new matrial to the course.

创建者 Charlie B J

Nov 25, 2021

Incredible course. Thorough yet understandable for anyone interested

创建者 Paritosh B

Dec 5, 2020

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

创建者 Rohan H J

Aug 2, 2021

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

创建者 Shivender K

Jan 23, 2021

Very complex specialization but significantly helpful

创建者 Samuel H K

Mar 4, 2021

Awesome course! Direct application to my research!

创建者 nghia d

Dec 21, 2020

amazing course! thanks coursea, thanks Instructors

创建者 Evgenii T

Jan 31, 2021

Easy yet fundamental enough for an eager learner.

创建者 Shams A

Jul 22, 2021

Amazing course. Thanks so much for offering it!

创建者 Ali G

Jul 22, 2021

Very informative and easy-to-understand!

创建者 Gokulakannan S

Dec 26, 2020

Nice course enjoyed it a lot. Thanks!

创建者 James H

Nov 17, 2020

Very thorough and clearly explained.

创建者 Xiaoyu X

Aug 1, 2021

Very good lectures and assignments!

创建者 Emmanuelle S

Jun 29, 2023

Excellent conclusion to the series

创建者 Kenneth N

Jun 27, 2022

exceptional and clear instructions

创建者 Parma R R

May 10, 2023

Very good and well design course!

创建者 Jesus A

Nov 22, 2020

Great applications cases of GANs

创建者 Linjun Y

Aug 17, 2022

Great course for everyone!

创建者 Dela C F S (

Jun 6, 2021

Full of amazing content! :D

创建者 Manuel R

Mar 30, 2021

It was a nice experience!

创建者 amadou d

Mar 11, 2021

Excellent! Thank You all!