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Отзывы учащихся о курсе Convolutional Neural Networks от партнера

Оценки: 40,448
Рецензии: 5,359

О курсе

In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more. By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Лучшие рецензии


3 сент. 2020 г.

Great course. Easy to understand and with very synthetized information on the most relevant topics, even though some videos repeat information due to wrong edition, everything is still understandable.


11 июля 2020 г.

I really enjoyed this course, it would be awesome to see al least one training example using GPU (maybe in Google Colab since not everyone owns one) so we could train the deepest networks from scratch

Фильтр по:

4826–4850 из 5,334 отзывов о курсе Convolutional Neural Networks

автор: Nemish K

8 дек. 2017 г.

The duration of the course was less, which made it very fast paced

автор: Clément R

13 июля 2019 г.

The course is very good. However some bugs remain in the notebook

автор: Keith L

16 июля 2018 г.

great course although the auto-graders could use some updating...

автор: Simon T

23 апр. 2021 г.

The parts on face verification and recognition are really short.

автор: Mohammed F S

12 сент. 2020 г.

Needs to be updated with current version of Tensorflow and keras

автор: Andrew N

19 авг. 2020 г.

most of the tensorflow documentation link is not working anymore

автор: Kartikey S

16 июня 2021 г.

The course was great overall. The assignments were easy though.

автор: João M A d S

12 июля 2020 г.

Face recognition week was too short to understand key concepts.

автор: Sandeep P

14 июня 2020 г.

Tough on programming side, but good videos. Learning was a fun!

автор: Antoine V

5 сент. 2018 г.

Very interesting, but the exercises should be more challenging.

автор: E W

11 февр. 2018 г.

One star less because the last homework notebook is very buggy.

автор: Prabhat A

28 дек. 2017 г.

Very insightful and interesting

Minor editing bugs in the videos

автор: Taimoor D K

29 авг. 2019 г.

Great course for those wanting to learns CNNs in a short time.

автор: Kenneth L

16 июня 2019 г.

Some sentences get repeated twice maybe due to editing errors.

автор: Michal M

8 февр. 2018 г.

It is very algorithmic base missing some deeper understanding.

автор: Manish C

5 февр. 2020 г.

Like always best course in computer vision by Andrew NG

автор: Tjalf B

27 июля 2019 г.

A great course with challenging tasks and great explanations.

автор: Jingxian L

8 мая 2018 г.

It's hard to debug when we don't get score on my submissions.

автор: Ankit K

10 дек. 2017 г.

The content is good but the assignments have a lot of errors.

автор: Ben R

3 авг. 2020 г.

A few bugs in the assignment grading, otherwise nice course.

автор: 紫色人的心

13 мая 2019 г.

The programming job doesn't feel well guided by the content.

автор: Fady E

18 февр. 2019 г.

there are some mandatory lessons that i feel are unnecessary

автор: Paul A

25 нояб. 2018 г.

a little bit hard to complete! But I liked it a lot, thanks!

автор: Kabakov B

27 авг. 2020 г.

Theory is good -- Ng the best. But programming tasks on TF1

автор: Aniruddh B

5 мая 2020 г.

Great course. Assignments too easy -- too much handholding.