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Вернуться к Convolutional Neural Networks

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

4.9
звезд
Оценки: 39,862
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

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.

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.

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4976–5000 из 5,240 отзывов о курсе Convolutional Neural Networks

автор: Achille H

6 июля 2020 г.

Great content, veerything is clear and concise. Only downside is the grading of the exercises, which sometimes requires you to use a very specific syntax (even though another syntax gives the exact same results) and causes hours of painful debugging and reading through the forums.

автор: Patrick C N

2 февр. 2020 г.

Model implementation is abstracted in many exercises. Many helper functions are created to just make things work. TensorFlow feels a little foreign still, not enough of an overview. Higher level APIs like Keras and/or PyTorch might do better here instead of mixing in TF randomly

автор: Cristina B

7 февр. 2018 г.

The last two weeks sometimes bored me and sometimes I had hard time in doing the assignments. The intuition behin object detection/face recognition and neural style transfer are well explained, but some more details for understaing how these models work is missing in my opinion.

автор: ALEXEY P

28 июня 2019 г.

The lecture content is good but the programming exercises are not explained well. Quite often you are left on your own to go through Keras and TensorFlow documentation. So, don't expect much help in learning how to implement the theoretical ideas explained in lectures.

автор: Richard S Z

27 апр. 2018 г.

The lectures are very good. The programming assignments are sometimes infuriating and do not add to an understanding of the subject at hand. More can be done to explain the Tensorflow and Keras code. Also complete code explained line by line would be VERY helpful.

автор: John

26 июня 2018 г.

I learnt a lot in this course, but i have the feeling that my knowledge is still very shallow specially when it comes to convolutional neural network design, i cannot tell pros and cons of each design and how to come up with new design that meets my use case.

автор: Esmaeil K G

1 дек. 2020 г.

Thank you for your great course, but, to me, it has a great problem. It proposed the general theory of ConvNet and then explained some applications on ConvNet. there was nothing in between, i think it could be better if ConvNets were explained more deeply.

автор: Linying M

22 февр. 2018 г.

The course is really good, but the assignment grader is a disaster. I spent days and nights reverse-engineering the expected codes, read the forums, only to pass the course before subscription expires, and this is certainly a very disappointing experience.

автор: Dushyant K

14 июля 2019 г.

I wanted to give five star; however, I could not. The function "model_nn" in Week-4. assignment -1 has been very poorly designed/ poorly explained. When I searched the forum, there are numerous questions on the same topic; but,, there was helpful hint.

автор: Sambit M

1 июня 2019 г.

Bugs in the template code cause a lot of time waste.

Also, the exercises need to be better which teach how to actually build a model ground up rather than just filling in small parts.

Getting the main models working is the key, which is not covered here.

автор: Max S

12 янв. 2018 г.

A great course, but I can't give it 5 stars... There's just too many broken assignments, the videos are barely edited, staff completely ignores discussion forums, and it generally feels a little unpolished. I'm sure this will improve in the future.

автор: Ankit J

12 сент. 2020 г.

Videos are great and give a strong understanding of the concepts, but the programming exercises are underwhelming. I don't particularly feel confident about the hands-on understanding of the concepts after complete the somewhat shallow exercises.

автор: JiahuiWEI

14 мар. 2019 г.

Improve the quality of vedio please. there are too much repeats that could be easily avoided, it much worse than the first two courses, not about the centent, but the vedio itself, is your workers seriously correct the probleme of vedio??????

автор: Deep M

12 авг. 2020 г.

The course was great but only the first two weeks were sufficient for me as a Mechanical Engineer. I am not really interested in localisation and face recognition. Also, high time that you should update to Tensorflow 2.0 for your exercises.

автор: Piotr P

9 июля 2021 г.

Great course, but assignments are from trivial to insane.

I would like to learn the ideas, but spending like 10 hours "learning" names and grammar of some packages, that will probably be outdated in next few years, is nothing fun for me.

автор: Marco K

17 февр. 2018 г.

What I really liked about the course was the actuality of the paper. However, I would have thought it absolutely necessary to explain the BackProp for CNNs. Also the grader problems in the last assignment force me to subtract two stars.

автор: Francesco B

30 нояб. 2017 г.

Face recognition notebook has a bug, I passed the grader but the function triplet_loss returned the wrong value in the notebook. Several other people have had this problem despite the fact that the notebook was supposed to be updated.

автор: A O

22 мая 2020 г.

Assignments do suck.

If model cannot be run locally there is no way to debug it. More test cases that would cover most common mistakes would be quite useful. Otherwise the only way through is to burry into forum topics for hours.

автор: Rosario C

4 янв. 2018 г.

The lectures were messier compared with the previous courses. Lot's of problems with the grading tools. The content of the course is great, so I would recommend it to others, modulo warning the others about being more patient :)

автор: Patrick S

26 дек. 2020 г.

This is one of the weaker courses in the specialization. I wish it had gone more in-depth. It's so far the most complex problem and I don't feel like it has gotten the same attention as the basics did, in the other courses.

автор: G C

24 мар. 2018 г.

Covers interesting material and practical problems, and tries to get the student to implement useful tools, but there is a large disconnect between the understandable theory and frameworks used to implement the solutions.

автор: Victor P

29 нояб. 2017 г.

Good course, but with the conjunction of the poor quality of the Coursera interface, video quality, the price does not feel like a great bargain. Still I feel confident I can be efficient after following this course.

автор: Sebastiano B

21 окт. 2019 г.

Exercises were purposly difficult because of obscure API documentation and quirks (not because the problem itself was difficult). Good school in debugging, I personally disagreed with it (V3 if I remember correctly).

автор: Rob W

14 мая 2018 г.

Enjoyed the course but the programming assignments weren't well designed I think. They were more about debugging than applying what was learned. I preferred the assignments of the earlier courses of this curricilum

автор: Lavínia M T

26 нояб. 2020 г.

The Face Recognition lab just don't make any sense, the expected outputs are the ones in the Face Recognition for the Happy House. And it made the exercise very annoying! Despite it, the course is really good.