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

4.9
26,359 notes
3,183 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

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.

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.

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3026 - 3050 sur 3,146 Examens pour Convolutional Neural Networks

par Roya K

Dec 08, 2017

content was good,Yolo was hard and i still does not suggest,wasted too much time on exercises,when the answer was not match it passed! very bad experience with the exercise part.

par Sudhanshu D

Apr 09, 2018

Week 3, exercise 2 is very buggy. Couldn't have completed it without the discussion forum. Kindly fix it for the future learners

par Mark P

Dec 09, 2017

The content covered is excellent as with the other courses.

However the material in this videos etc have many editing glitches. In addition some of the notebook based programming assignments are misleading and have minor errors that caused auto-grader issues.

In addition the programming assignments seem to be dumbing down. You spend lots of timing solving syntactic nuances of tensorflow, Keras etc rather than being asked to solve cerebral problems that help understanding of the concepts.

par Carmine M

Apr 12, 2018

Very interesting and with high quality material. It could be improved by adding more tutorials about the frameworks used.

par Rüveyda K

Mar 17, 2018

Sometimes it was very difficult to understand lecturer because of his accent, but apart from that, assignments and lessons were helpful

par Pavao S

Mar 02, 2018

Not enough theory

par Johannes A B

Mar 26, 2018

Very good covarage of the algorithms when it comes to analyzing pictures, and a good intro to the theory behind the models. But it is too little emphasis on other uses of convolutional networks like 1d convolutions, causal convolutions and similar. Maybe there are some coverage of these topics in the sequence course in the series, but it should be covered here to a larger extent either way.

par Francesco B

Nov 30, 2017

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.

par Anthony M

Dec 04, 2017

Great class and amazing assignments. I really enjoyed learning about CNNs, YOLO, and Neural Style Transfer.

Errors with submitting the assignments, particularly weeks 2 & 4 took away considerably from the overall satisfaction with the course.

Thank you once again for providing a rich learning environment. :)

par Cristina B

Feb 07, 2018

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.

par Alan P

Dec 09, 2017

Too much bugs in program assignment and sometimes the instructions are not clear!!

par Xiaohua Z

Jun 11, 2018

Terrible grading system waste u tons of time.The content itself is excellent.

par rudy F

Nov 23, 2017

course was good but server/grader bugs in the programming tests were demotivating...

par Tatsunari W

Mar 28, 2018

A great introductory course in CNN

A little too many hints and too much guidance on every coding assignment

par Murad O

Nov 17, 2017

I have mixed feelings about this course in particular, although one learns many interesting and useful concepts, I did little implementation on my own. Also the involvement of Keras I found annoying, yes it eases the implementation of ConvNets, but while learning I would have preferred to use tensor flow instead, or even implement a simple NumPy ConvNet on my own.

par Antoine H

Dec 07, 2017

Several bugs in the last programming assignment

par Claire L

Mar 04, 2018

Content was great but the grading issues with the homework assignments made this course very time consuming and frustrating. Will recommend it when grading issues are fixed.

par Serkan Ö

Jun 10, 2018

There were repeats in the videos🤔 Also the answers to quizzes are not visible. If these would have existed, 5 stars would be reasonable.

par Aoun L

May 29, 2018

The course is great but the assessments and grading is terrible, so many particularities and repetition that does not make sense.

par Yi-Hao K

Jan 20, 2018

Serious bug in assignment

par Kim Y

May 14, 2018

need to teach us more about tensorflow to do last week's assignments

par zz

Mar 05, 2018

没有翻译 tenserflow也讲得不好

par Tom B

Jul 24, 2018

programming assignments are of lower quality than previous sections of the course

par Hagay G

Apr 26, 2019

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.

par ALEXEY P

Jun 28, 2019

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.