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学生对 提供的 Convolutional Neural Networks 的评价和反馈

40,448 个评分
5,359 条评论


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....



Sep 3, 2020

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.


Jul 11, 2020

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


5276 - Convolutional Neural Networks 的 5300 个评论(共 5,334 个)

创建者 Daryl V D

Jun 19, 2018

TOO MANY BUGS IN THE EXERCISES.It was a dis-incentive. Really.And I love me some! It has been great. The videos and content structure are fantastic.

创建者 Arsh P

Dec 15, 2018

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.

创建者 Yongseon L

Jun 15, 2019

创建者 mike v

Jun 8, 2019

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

创建者 Sébastien C

Aug 18, 2020

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

创建者 Joshua S

Nov 29, 2019

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

创建者 Kristoffer M

Nov 30, 2019

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

创建者 Prasenjit D

Dec 6, 2017

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

创建者 Sandeep K C

Dec 28, 2018

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

创建者 I M

Oct 17, 2019

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

创建者 Shuhe W

Jun 8, 2019

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

创建者 Bernard F

Dec 13, 2017

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

创建者 Ryan B

Jan 2, 2020

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

创建者 Coral M R

Jun 7, 2019

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

创建者 Jason K

Dec 13, 2017

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

创建者 Mike B

May 7, 2018

Good course but lots of technical issues with the assignments.

创建者 Kishan

Feb 13, 2018

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

创建者 Stéphane P

Mar 30, 2019

Videos are good, but exercises are really confusing

创建者 chao z

Feb 22, 2018

content good, but assignment is in poor quality

创建者 hossein

Jul 19, 2020

The structure of the assignments is not good

创建者 Ankur S

Dec 30, 2019

Programming exercises have bugs

创建者 borja v

Aug 22, 2019

unclear content...I'm sorry

创建者 Alex A K

Sep 28, 2019

Numerous technical issues

创建者 Christopher H

Feb 24, 2022

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.

创建者 Mostafa A

Dec 16, 2017

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.