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Вернуться к Convolutional Neural Networks

Отзывы учащихся о курсе Convolutional Neural Networks от партнера deeplearning.ai

4.9
звезд
Оценки: 39,859
Рецензии: 5,270

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

AR
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

RK
1 сент. 2019 г.

This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.

Фильтр по:

5176–5200 из 5,240 отзывов о курсе Convolutional Neural Networks

автор: Stoyan S

29 июля 2018 г.

Some of the topics were not explained in enough detail and felt like being quickly skipped. There were some problems with the grader system in one of the assignments which wasted a lot of time and caused frustration.

автор: Bryan L

21 янв. 2018 г.

Content was great but a very buggy grader in week 4 made for a stressful experience that upset many students. Grader bugs caused me to repeat the course in another session and those bugs remained in the next session.

автор: Oswaldo B F

1 дек. 2017 г.

Programming assignments did not deal directly with the CNN models, but with auxiliary functions. Hacking the grader was more important than getting the right answer. Videos should have been better edited too.

автор: Vihar K

6 июня 2018 г.

Lectures are awesome, really inspiring and intuitive.Trouble with submitting assignments. I've solved the given question and resubmitted for almost six times, but the kernels showing up errors.

автор: Carlos E L

12 июля 2018 г.

Horrible user experience with the "Jupyter Hub" constant issues that makes trying to do the exams an absolute nightmare and a perfect anxiety booster!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

автор: Dario d J B U

15 нояб. 2019 г.

In some tasks the delivery format is arbitrary and does not specify well what is wanted, that is, so the numerical value requested is good, the output is incorrect. due to format issues.

автор: Aman B

23 июля 2020 г.

Programming part was not explained well. I guess programming syntax and flow of code should be explained too instead of just telling theory or focusing mainly on theory.

автор: Daryl V D

19 июня 2018 г.

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

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.

https://www.coursera.org/learn/convolutional-neural-networks/programming/IaknP/face-recognition-for-the-happy-house/discussions/threads/NcpP7i95EemJswr-eOHMNg

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