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Отзывы учащихся о курсе Convolutional Neural Networks от партнера

Оценки: 40,434
Рецензии: 5,358

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


12 янв. 2019 г.

Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.


11 дек. 2019 г.

Great Course Overall\n\nOne thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.

Фильтр по:

5276–5300 из 5,333 отзывов о курсе Convolutional Neural Networks

автор: Arsh P

15 дек. 2018 г.

Though the videos were very good but the assignments require too much from us and also there are few mistakes in week 3 and 4 notebooks which take a lot of time.

автор: Yongseon L

15 июня 2019 г.

автор: mike v

8 июня 2019 г.

The content is excellent, but there were technical problems with the final homework assignment that were not addressed by staff in a timely manner.

автор: Sébastien C

18 авг. 2020 г.

Content was interestind and provided good theoretical overview. Exercices where you just have to fill in some line of codes are not usefull.

автор: Joshua S

29 нояб. 2019 г.

Some of the code was incorrect and the guidance was often confusing. Visibly worse than the other courses in the specialization,

автор: Kristoffer M

30 нояб. 2019 г.

Don't feel like I understand these models much better than before. Still don't see the logic of the identity layers

автор: Prasenjit D

6 дек. 2017 г.

Lots of problem with the grader. Wasted a lot of time grappling with grader issues. Very disappointed.

автор: Sandeep K C

28 дек. 2018 г.

The quality of some of the graders e.g. IOU is poor. One cannot make out what exactly is it checking

автор: I M

17 окт. 2019 г.

Disappointed by the quality of notebooks, which often disconnect and lose all the code you wrote.

автор: Shuhe W

8 июня 2019 г.

The course assignment parts have many errors, I have to fix it myself. That's silly.

автор: Bernard F

13 дек. 2017 г.

Good content, but quite a bit of technical work is needed to present this better.

автор: Ryan B

2 янв. 2020 г.

for goodness sake "your didn't pass the test" isn't feedback for notebook grades

автор: Coral M R

7 июня 2019 г.

Dificultades en la hoja de tareas de Face Recognition que deberían solucionar

автор: Jason K

13 дек. 2017 г.

The content was good, as usual, but week 4's quiz was pretty buggy.

автор: Mike B

7 мая 2018 г.

Good course but lots of technical issues with the assignments.

автор: Kishan

13 февр. 2018 г.

The notebooks were too simple. And the grader was not working.

автор: Stéphane P

30 мар. 2019 г.

Videos are good, but exercises are really confusing

автор: chao z

22 февр. 2018 г.

content good, but assignment is in poor quality

автор: hossein

19 июля 2020 г.

The structure of the assignments is not good

автор: Ankur S

30 дек. 2019 г.

Programming exercises have bugs

автор: borja v

22 авг. 2019 г.

unclear content...I'm sorry

автор: Alex A K

28 сент. 2019 г.

Numerous technical issues

автор: Christopher H

24 февр. 2022 г.

C​ustomer service informed me that once a user completes a course, they're not permitted to access the assignments for reference again. This is a huge drawback to this platform, as that's where the real lessons are and essentially prevents a paying customer from being able to reference their own work. This is esspecially dissapointing given that I would have followed the instructions to download the Jupyter notebooks while in the class had I know about this bizzarre policy.

автор: Mostafa A

16 дек. 2017 г.

Assignement: Face recognition for happy house was not happy at all

it took me 4 attempts to pass.

triplet_loss function you need to submit incorrect answer to pass. to get correct answer you need to have axis=-1. Bu to pass you have to take it out.

I hope you guys fix to stop more people to waste there time.

Not happy at all.

автор: Matteo V

6 июня 2021 г.

I​ took the basic ML course and now am taking all the Deep Learning courses. This is by far the worse course so far. Assignments are very unclear. Even explanations are less linear than in previous courses. Support is now on a different platform and not directly on Coursera. I would give it a negative grade if I could.