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Вернуться к Convolutional Neural Networks

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

4.9
звезд
Оценки: 40,632

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

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.

OA

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.

Фильтр по:

4651–4675 из 5,361 отзывов о курсе Convolutional Neural Networks

автор: Václav R

2 мая 2019 г.

Good introductory course. A bit more focus on transfer learning and using e.g. only a part of the networks would have been nice.

автор: Adam_Hua

27 янв. 2019 г.

the content of course is quite good ,expecially the quiz and assignment.

But the server of programming assignment is quite slow.

автор: Aadesh N

12 нояб. 2017 г.

Excellent course with great materials. In my view, the difficulty of programming assignment needs to a bit harder that it is now

автор: Ryan L

12 июня 2018 г.

Great content but the slow speed and iffy stability of the jupyter notebooks makes the assignments a bit of a pain to complete.

автор: Alex

1 янв. 2018 г.

Some bugs in grading will make you to waste 3-4 hours of time, which is frustrative. All except this is quite good and valuable

автор: Thành C V

17 нояб. 2019 г.

I really like this course. It gives me a huge of fundamental knowledge about CNN. Special Thank to PhD. Andrew Ng and mentors.

автор: Victor v d B

14 янв. 2018 г.

Superb content, and a great course! Unfortunately issues with the assignments keeps this from a 5 star course when I took it.

автор: Galib M

21 февр. 2020 г.

Thanks for another well organized course. It would be nice if there were more details about building and training the model.

автор: Jonathan H

16 авг. 2020 г.

Good and very comprehensible, but does not go into depth. Particularly, homework assignments should give better practice...

автор: Tōnis S

27 мая 2020 г.

Great course. Maybe videos and assignments we not as good as in first three courses, but still very informative and useful.

автор: Shivam S

2 июля 2019 г.

Good Course but they should also teach how to implement transfer learning and how to load the dataset.

Anyway a good course.

автор: Gaetan J d B

9 июня 2019 г.

awesome content. some issues with assignments but nothing major...

Continuing on the next course, like them a lot! Txs guys.

автор: Thomas

15 янв. 2018 г.

The course content is very interesting.

Only 4 stars because of the frustration due to the bugs in week 4 graded assignments

автор: Sekib O

31 дек. 2017 г.

I have learned a lot but still don't feel confident when it comes to building CNN from scratch or choosing hyperparameters.

автор: Jörg P H

24 нояб. 2017 г.

great course again, but despite updated notebooks still some errors. Thanks to the community for communicating and sharing.

автор: Edward D

20 нояб. 2017 г.

The course is great, Andrew explains everything in CNN very clearly. But the assignment and grader really need some update.

автор: Dr M B N M

26 мая 2020 г.

Learnt CNN with practical examples. But it would have been good if tensor flow, keras part also might have been explained

автор: Ankur B

8 апр. 2020 г.

Awesome course! I would highly recommend this to anyone who is an AI enthusiast specially in the field of computer vision.

автор: Adit S

30 нояб. 2017 г.

It would have gotten five stars, but grading problems and other technical difficulties on the backend were very prevalent.

автор: ARJUN K V

10 авг. 2020 г.

an awesome and necessary course for deep learning aspirants. Taught well and thanks to all the team for this opportunity.

автор: Lech G

19 июня 2020 г.

The course is very good, but I find that the mixture of numpy, tensorflow and keras in the assignments is quite onfusing.

автор: Simon G

25 апр. 2020 г.

I still love andrew, my only problem with this course was that it was quite shallow. There were a lot of editing mistakes

автор: Daniel F

4 янв. 2020 г.

I would have appreciated a little more depth in the programming exercises but otherwise a good introduction to the topic.

автор: Tung N

14 янв. 2018 г.

The grader is unfortunately still not fixed for triple_loss function even though the comment in the notebook was correct.

автор: Varun

6 февр. 2021 г.

I will rate it as 4 stars. Because the course has just one lacking point It does not give enough insights in Tensorflow