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學生對 deeplearning.ai 提供的 Convolutional Neural Networks 的評價和反饋

4.9
40,442 個評分
5,359 條評論

課程概述

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....

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AR

2020年7月11日

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

RS

2019年12月11日

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.

篩選依據:

5076 - Convolutional Neural Networks 的 5100 個評論(共 5,334 個)

創建者 Linying M

2018年2月22日

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.

創建者 Dushyant K

2019年7月14日

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.

創建者 Sambit M

2019年6月1日

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.

創建者 Max S

2018年1月12日

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.

創建者 Ankit J

2020年9月12日

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.

創建者 JiahuiWEI

2019年3月14日

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??????

創建者 Deep M

2020年8月12日

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.

創建者 Piotr P

2021年7月9日

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.

創建者 Marco K

2018年2月17日

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.

創建者 Francesco B

2017年11月30日

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.

創建者 A O

2020年5月22日

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.

創建者 Rosario C

2018年1月4日

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 :)

創建者 Patrick S

2020年12月26日

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.

創建者 G C

2018年3月24日

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.

創建者 Victor P

2017年11月29日

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.

創建者 Sebastiano B

2019年10月21日

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).

創建者 Rob W

2018年5月14日

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

創建者 Lavínia M T

2020年11月26日

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.

創建者 Denys G

2017年12月3日

The production of the course felt rushed, there are numerous clipping issues in the videos and a major bug in one of the assignments. Also, for such a key topic to be covered in only 4 weeks felt very shallow.

創建者 E S

2018年1月21日

Good explanations of the material but bugs in homework assignments and better explanations of tf usages is required for certain assignments. A refresher of tf via an additional assignment would've been nice.

創建者 Daniel M

2018年1月27日

Good insights on the YOLO algorithm as well as in Siamese networks and triplet loss. Miss some more deeper understanding both in the lectures and the assignments, but I totally recommend the course anyway.

創建者 ashwin m

2019年7月22日

very good topics discussed ,facial recognition and facial verification assignments do not do justice to the complexity involved.practical knowledge gained is less compared to other modules prior to this.

創建者 Carlos V

2020年7月16日

The knowledge is good, and the techniques taught are valuable; however, having to use a deprecated version of TensorFlow is annoying and a lot of this will have to be re-learned to be put into practice.

創建者 Hagay G

2019年4月26日

Course is very informative.

Unfortunately, unlike other courses in the spec, there were quite a few bugs in the notebooks and they took quite a while to load due to the sheer weight of the models loaded.

創建者 David v L

2018年1月2日

Face recognition is a bit oversimplified, there is more to it that a simple accuracy metric. Priors are involved, which are included in the NN training, but should really be disassociated in evaluation.