Chevron Left
Back to Convolutional Neural Networks

Learner Reviews & Feedback for Convolutional Neural Networks by DeepLearning.AI

4.9
stars
42,028 ratings

About the Course

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....

Top reviews

RK

Sep 1, 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.

OA

Sep 3, 2020

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.

Filter by:

4626 - 4650 of 5,570 Reviews for Convolutional Neural Networks

By Gary S

Nov 22, 2017

Great material, but there was a bug in the grading of the final problem. To work around the bug in the grader, everyone is modifying their program so it doesn't match the expected results but nonetheless will pass the grader.

By איתי ק

Dec 13, 2020

I think that you should give more details and instruction how to implement our own images, how to perform Transfer learning to the ConvNet for improving, how to train the network myself not only load the pre-train network...

By wilfried l

Apr 11, 2020

Very Interesting

As usual, it is very very good from theory point of view. Practical examples are also really interesting.

Do not expect to be autonomous after the course, as you won't be able to use Tensorflow or Keras alone.

By Benny P

Mar 29, 2018

This course provides great introduction to CNN. It is an eye opener if you didn't know about CNN and it will take you to a level where you will be quite comfortable with CNN formulas and know a bit about how to implement it.

By Van V N

Dec 8, 2017

I learned a lot about CNN. Good programming assignments. Unfortunately the quality of this course was not as good as the three courses before (Grader Bug in last programming assignment, see discussion forums for workaround).

By Заспа А Ю

Mar 29, 2021

Вообще четко, еще бы отредактировать субтитры на английском. И цены не будет. Звезду снимаю только за то, что когда описывается модель с распознаванием и позиционированием начинается сумбур и надо по несколько раз смотреть.

By Paulo V

May 25, 2018

Great lectures and exercises but the leave-behind study materials (lecture slides and notebooks) could be a little more helpful, and the frequent server disconnects have forced me to do most of the programming work offline.

By Iurii L

Sep 1, 2022

A lot of useful information.

However, video editing is awkward sometimes plus Andrew's voice sometimes gets down to wisper which is hard to catch.

So good course but there is defenitely some spave to improve presentation.

By Nitin C

Dec 11, 2019

Loved the content. Covers the fundamentals of ConvNets wonderfully. Need a lot more clarity on the use of TensorFlow and Keras in building these systems. Particularly the programming exercises felt a little obscure to me.

By Anupam

Jun 13, 2023

Although the course is comprehensive, at times, some of the concepts were skimmed over, especially in weeks 3 and 4. Topics like UNet architecture and Neural Style transfer felt rushed.

Overall, the course was excellent.

By akshaya r

Apr 12, 2020

Great Course! I did the sequence model course before CNN. CNN programming exercises are challenging than the other four courses but could solve it with the support of discussion forums and hints provided in the exercise.

By jianguang

Aug 1, 2019

the general concept is important to understand the data flow from one block to anther block. this will give me big picture to learn convolution Neural Net works , thanks all content and support on this course.

-jianguang

By Shane M

Feb 2, 2018

I had to watch the videos more than once to grasp all of the material. The exams were harder, and no partial credit was given nor specific indication of missed questions on the quizzes. Great material, very applicable.

By Nicolas T

Jan 5, 2018

The lectures are awesome as usual, but I would prefer less guided exercises with less fancy content but more I don't feel like I have implemented anything myself unfortunately. Still, big thanks for the great pedagogy!

By Amit A

Nov 18, 2017

Not as great as the previous three.

Prof Ng's explanations are flawless and awesome as always but the programming assignments had more issues but I think by the time others take this course all issues will be resolved.

By 李磊

Nov 28, 2017

The judge system of last week's work has some problem, but the course of Andrew is still worthy to learn. Learned a lot about CNN from the course, but still need to read more papers in order to step into the field.

By Raghav B

Jan 17, 2019

This is a great course with a lot of useful content. The only reason I am not giving it 5 stars is that it was too packed. I would suggest Andrew and team to convert this course to a 6 week course instead of 4 weeks.

By Scott M

Apr 17, 2018

Overall the Course is good but the only examples given in assignments or lectures pertain to Computer Vision and Image recognition/manipulation. Surely a few examples or discussion of other uses of CNNs is in order.

By Dilan E D G

May 23, 2021

Really good, got stuck on some parts but I got the help I needed, also the last week was very interesting :)

P.d. : The quizzes needs more feedback, because sometimes I didn't know why I was wrong at some questions!

By Aki N

Feb 8, 2018

Otherwise an excellent course, but the programming exercises were a little trivial. Then again, wouldn't have a suggestion as to how to make them more challenging without blowing up the required time spent on them.

By Jairo L D A

May 22, 2018

Great course and content, but some assigments were too "deep" in difficulty. Not that difficult things can't be asked, but the jumps could have been a little better adjusted. But overall the course was very nice.

By Thorben P

Aug 26, 2020

Lecture material is great. One suggestion from my side would be to spice up the facial recognition programming assignment a bit. To me it felt like all the magic would be hidden in the img_to_encoding function.

By Benoit D F

Dec 10, 2017

Great course content but frankly compared to Andrew's ML and the past 3 courses, the polishing of the notebooks assignments was not there and I wasted a lot of time fixing errors that were not helpful to learn.

By Alexandru S

Aug 3, 2019

The course itself is fine and is probably what most students enrolled for but Coursera is unacceptably broken. Had much greater technical problems with the programming assignments than any other course so far.

By Jiaxuan L

Dec 21, 2017

I enjoy almost all of the contents in this course. Very nice introduction to CNN. The only problem is that the last assignment for face recognition is filled with bugs. That's why I gave a 4 star instead of 5.