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Вернуться к Build Basic Generative Adversarial Networks (GANs)

Отзывы учащихся о курсе Build Basic Generative Adversarial Networks (GANs) от партнера deeplearning.ai

4.7
звезд
Оценки: 1,520

О курсе

In this course, you will: - Learn about GANs and their applications - Understand the intuition behind the fundamental components of GANs - Explore and implement multiple GAN architectures - Build conditional GANs capable of generating examples from determined categories 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....

Лучшие рецензии

HL

10 мар. 2022 г.

Great introductory to GANs, focused on the building blocks to neural net/ GANs, and a bit of frequently used models. Might need a small update on what's considered "state-of-the-art" in the course.

WM

1 окт. 2020 г.

The course provides good insight into the world of GANs. I really enjoyed Sharon's explanations which were deep and easy to understand. I really recommend this course to anyone interested in AI.

Фильтр по:

201–225 из 373 отзывов о курсе Build Basic Generative Adversarial Networks (GANs)

автор: Joyce Y

7 нояб. 2020 г.

quite easy to follow! assignment is well explained!

автор: null j

23 сент. 2021 г.

a very impressive introduce for a beginner in GANs

автор: Nazmus S

7 июля 2021 г.

great content to learn quickly hands on about GANs

автор: Julien

17 окт. 2020 г.

Un cours impressionnant par sa clarté. J'ai adoré.

автор: Евгений Ц

31 янв. 2021 г.

Easy yet fundamental enough for an eager learner.

автор: Victor v d B

8 окт. 2020 г.

Super easy going introduction into GANs. Thanks!

автор: M. H A P

30 мар. 2021 г.

Excellent course to gain my knowledge about GAN

автор: Neeraj P

28 дек. 2020 г.

Really helps demystify GANs and how to use GANs

автор: Wong H S

11 дек. 2020 г.

Very detailed and attractive course, thank you!

автор: Ibrahim S

21 янв. 2021 г.

Great content presented in a very simple way.

автор: Ammar T

6 нояб. 2020 г.

Exceptionally well and I like the fourth week

автор: Adam M

12 июня 2021 г.

Amazing intro to GANs and well prepared labs

автор: Ahsan G

29 окт. 2020 г.

It was a really fun and interesting course.

автор: JP A

12 нояб. 2020 г.

Exciting start to the GANs Specialization.

автор: Gustavo M

6 окт. 2020 г.

Excellent. Best Lectures & Great Professor

автор: Mikhail O

28 дек. 2020 г.

Coding problems could be more challenging

автор: Deleted A

1 дек. 2020 г.

Loved this course. Such a practical one.

автор: Matjaž M

2 янв. 2021 г.

Great course, very clear and organised!

автор: James H

16 окт. 2020 г.

Well-articulated and well-paced course.

автор: farzaneh n

22 авг. 2021 г.

Great course with thorough discussions

автор: Tianqi T

28 апр. 2021 г.

very intuitive lectures and assignment

автор: sumit c

21 янв. 2021 г.

The curriculum was easy to understand.

автор: JISHA R r

3 дек. 2020 г.

Excellent classes. Found very useful.

автор: Wenyan T

21 сент. 2021 г.

Sharon is such a great instructor!!!

автор: Deleted A

25 янв. 2021 г.

Very interesting and powerful course