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Avis et commentaires pour l'étudiant pour Convolutional Neural Networks par deeplearning.ai

4.9
25,494 notes
3,069 avis

À propos du cours

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization....

Meilleurs avis

AG

Jan 13, 2019

Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.

RK

Sep 02, 2019

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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2951 - 2975 sur 3,034 Examens pour Convolutional Neural Networks

par Uddhav D

Jun 07, 2019

Some issues regarding the submission of assignments and some minute mistake in the videos and assignment. Although great teaching by Andrew as always :)

par Luis F A

Jun 09, 2019

Theoretical content was very informative and high quality. However, some problems with the programming assigments were annoying. For instance, for the last programming assigment some weights would not load and it was necessary to go get the weights from the github repository of some other person.

par Bingcheng L

Jul 14, 2019

Not enough materials about the fundamentals about CNN, just a couple of implementation without details.

par Dushyant K

Jul 15, 2019

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.

par Mostafa M

Aug 30, 2019

The last week (week 4) was not explained in enough detail. I was often frustrated because i was finding myself not fully understanding the concepts because of missing details.

par Yair S

Sep 07, 2019

While the online teaching of Prof. Ng, is excellent as in the other courses, this course specifically, has several pitfalls which can not be ignored:

1) The teaching and cover being given for TensorFlow are by far insufficient. If this subject is seen as an essential part of the course, it must be instructed systematically but this is not the case, unfortunately. More often than not, you find yourself doing guesswork in the assignments when it comes to TF code, which is also reflected in the Discussion Forum. So to summarize, TF must be covered in a systematic way, either in this course, or a previous one.

2) There is a bug on week 4 NST assignment, on the given code. Should be fixed.

3) There are several written correction to errors in OnLine videos. These Videos can and should be rerecorded.

4) Last but certainly not least: I have experienced frequent and really disturbing connection problems with the Python Notebook, with frequent connection errors, which can not be recovered and wherein one must open again the Notebook. While this was, to some extent, the case in other courses, in this course it was much more of a problem, especially in Week 4, probably due to a large amount of data, and where each rerun requires another 20 - 30 minutes. a MUST fix.

Thanks,

Y. Shachar.

par Stefan M

Jun 14, 2019

The homework assignments, compared to the other courses, where pretty low in quality. If these errors get corrected, I'd happily give this course 5/5 stars.

par Abhishek R

Sep 22, 2019

The course material is really good and Andrew explains things really well. However, the programming assignments cause a lot of problem owing to the performance of the grader where by correct answers are marked as incorrect/incomplete and the only option to submit the assignment OR get it graded correctly is to follow steps from the forums to make changes to the files to trick the grader in order to get it submitted. From the forums it seems like these problems have been there for over 2 years and still has not been fixed. Overall the programming assignments are really good and helps in understanding the implementations.

par Stefano F P

Oct 01, 2019

Too easy excercises and with an old version of tf

par Ankit R

Oct 07, 2019

Found it really difficult to submit programming assignments, at times the jupyter notebooks were not at all responsive.....

par 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.

par 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

par Stéphane P

Mar 30, 2019

Videos are good, but exercises are really confusing

par Oliverio J S J

Feb 03, 2019

This course is an interesting review about techniques of image recognition based on neural networks. Unfortunately, it is not possible to achieve a deep understanding of these techniques during the time the course lasts. The practical activities are just filling lines in programs following the provided instructions and, sometimes, it is even possible to do it without understanding the rest of the code. The frequent disconnections between the notebook and the server slowed me down a lot and even made me lose all my work and start from scratch several times.

par Alex

Nov 09, 2018

The first two sessions are very well explained, with clear and precise examples. However the last two sessions, are explained in a very superficial way, without a good example, the explanation of these sessions are not deepened, the practical exercises don't teach how the problem is really solved. To truly learn, it is necessary to go out searching the internet.

par Joshua O

Nov 14, 2018

The first couple weeks laid a good foundation for understanding CNNs, but I did not understand the point of diving so deep in to Computer Vision, especially having a lengthy programming assignment devoted to an algorithm as complex and relatively niche as YOLO. There are several different architectures/applications of Deep Neural Nets conspicuously absent from this entire sequence, most notably GANs and AutoEncoders. I felt a good deal of frustration when implementing the programming assignments in the latter half of this course

par Prasenjit D

Dec 06, 2017

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

par David C

Dec 24, 2017

Week 4 videos were not edited at all. Week 4 lecture slides were not available for download. Week 4 programming exercise grader had significant errors such that the incorrect solution needed to be coded in order to pass.

par Oswaldo B F

Dec 01, 2017

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.

par Jeff N

Apr 12, 2018

I feel this is by far the weakest of the first 4 courses in the series. The information is really valuable and the homework offers almost no opportunities to actually explore CNN architectures. The homework is more about implementing a few parts of a dictated network where all of the critical information is provided. The only exercises are in more vector manipulation and knowledge of frameworks that are never talked about in the actual course material. I'd love real framework material and real opportunities to practice using them, but the limited exposure here does not cut it.

Basically, I listened to the videos talk about CNNs, answered quiz questions about minor foot notes in the lectures, and then messed with vectors again. Oh, and the video editing was pretty choppy in this course compared to the others. Disappointed.

par Carlos E L

Jul 12, 2018

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

par Juan F R L

Feb 15, 2018

I found it very easy to go through the assignments and the quizzes were great, but I do have 2 complaints: -- I didn't get quiz feedbacks (they seem to be disabled), so, this is a huge let down and I wasn't able to completely grasp the concepts. -- For example the Gram matrix I had to accept it was true when they said "if the filters are quite similar then the dot product will be high". Show this please? #mastery #selfcontained. -- Another example, on the programming assignment, on Neural Style transfer, it is POORLY explained how the framework works when it comes to setting a_G and a_C. Then it is said "this will be covered (explained) in the "model" function, which wasn't. -- I have printed most of the mentioned papers and I am starting to read them, I loved the fact you recommended papers on this lesson, and the rest of the programming assignments were great, especially when you would provide "Hint" to go to the docs and lookup the method, etc.

par Stephen D

Dec 26, 2017

The videos need editing. Ng repeats himself in several places as he tries to explain an idea. The programming assignments use too many global variables. The programming assignments real challenge seems to be in reshaping tensors when the reshaping is unnecessary. The wording of the problems in the quizzes needs improvement and clarification.

I liked the content. This course didn't feel polished like the others.

par Peter G

Dec 10, 2017

Assignment for Week 3 is just a load of BS. Complete mess with no structured attempt to explain relations between suggested data-structures and built-in functions that use them. Whole fairly nice course is completely ruined by this one mindless pile of 'fill in random line of code to get the result' approach.

On the top of that - a final cherry on the pie was complete mess with Week 4 assignment on face recognition. Multiple bugs in the assignment code and grading, broken db's for the notebook and complete lack of support from Coursera. A shame. Weak and shame.

par Roberto C

Nov 29, 2017

Very buggy, videos having problems (like repeating phrase), many errors in notebooks so that you spend more time trying to understand why grader doesn't work than on actual exercises...

The explications are either too simple or too sketched, so that you never really understand where difficulties are. The programming exercises are hard on the programming part and too easy on the math part, essentially what it is difficult is using tensorflow and keras with little or no explications.