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Вернуться к Build Basic Generative Adversarial Networks (GANs)

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

Оценки: 1,512

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


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.


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.

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176–200 из 372 отзывов о курсе Build Basic Generative Adversarial Networks (GANs)

автор: Shivender K

22 нояб. 2020 г.

I had a very good hand on experience on GAN with weekly assignments.

автор: AKASH C

9 окт. 2020 г.

A great introductory lesson on GANs. Coding exercises where amazing.


2 янв. 2022 г.

The Course material is very well presented and super easy to follow

автор: Злобин Я Н

8 июля 2021 г.

Its greate course to start studying GAN's model and architecture

автор: Junaid W

30 мая 2021 г.

Well Organized and to the point course. Thank you for making it

автор: Kejung H

3 апр. 2021 г.

Let me have a basic full understanding of GANs in a short time.

автор: Amr A

9 окт. 2020 г.

Well organized and informative course on GANs. Thanks very much

автор: Sumera R

26 нояб. 2021 г.

Excellent course for those who want to delve into GAN's world.

автор: Adarsh W

11 янв. 2021 г.

Great introduction to GANS but difficult programming exercise.

автор: Md. A A M

17 мар. 2021 г.

Best course. Best Instructor. Best Labs. Highly recommended.

автор: Rajinder S

7 мая 2021 г.

Absolutely engaging and digestible introduction to GANs!!

автор: Prasad V G S

28 февр. 2021 г.

Really useful to enhance my knowledge in the field of ML.

автор: Moonsu K

21 окт. 2020 г.

This was such a great course. Thanks for offering this.

автор: Ahmed S

9 нояб. 2020 г.

Really great course with a hands-on learning experience.

автор: Namas B

13 окт. 2020 г.

Phenomenal teaching method! Absolutely love this course.

автор: Sathvik S

10 окт. 2020 г.

Very good course ... Great Instructor, Good assignments

автор: Leonardo P

31 окт. 2021 г.

A good and fun introduction to GANs. Super cool videos.

автор: Bob K

25 февр. 2021 г.

Well constructed and explained. Very worthwhile course

автор: Aditya Y

15 нояб. 2020 г.

Fun course! I had a blast playing with various examples

автор: ZHOU T

7 окт. 2020 г.

A very instructive course of GANs, strongly recommend !

автор: Daniel A

10 нояб. 2021 г.

Great course! But the assignments were rather simple!

автор: Charles X

26 мая 2021 г.

It's a pretty good course to get familiar with GANs.

автор: Yiqiao Y

2 янв. 2021 г.

Highly recommended! I am learning a lot from Sharon!

автор: Ái N

16 февр. 2021 г.

Well-planned materials and easy-to-follow lectures.

автор: Joyce Y

7 нояб. 2020 г.

quite easy to follow! assignment is well explained!