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.
Dec 12, 2019
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.
by Chris M•
Aug 02, 2019
The assignments are less copy paste and some allow the student to explorer different NN architectures. However, most of the videos are still a waste of time. And the methods needed to complete the assignments aren't taught to the student. Instead you have to spend a lot of time searching and hoping you find the right method.
by André N•
Dec 02, 2018
video courses were really good, but the programming assignments drove me nuts. I am a senior software developer and I am writing software for more than 10 years now. I had a really hard time understanding the Tensorflow code. I think it is better to suggest a student to learn the basics of Tensorflow before doing this course
by Mladen M•
Jan 21, 2020
Couple of suggestions: 1) fix the artwork via neural networks assignment as there is a bug in your code 2) With the lectures I would suggest that you do a summary explanation of how the whole process works (all steps and motivation - a review) at the end of each group of lectures (one for artwork one for face recognition)
by Quoc B D•
Jun 12, 2018
The theory is very good but the exercise part is not good enough for me (For example in the Face Recognition exercise, I'd like to build (even a simple model) and train the triplet loss function... However, all that I can do is only loaded a trained model and then apply some simple similarity measure on encoding vector)
by Zach L•
Apr 09, 2018
videos are excellent and insightful as always. I thought the homework assignments for this section were the worst yet. simultaneously holding your hand so much you don’t do or learn anything meaningful, and also providing you with obscure or insufficient guidance in the moments when you’re asked to fill in the blanks.
by 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. :)
by 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.
by Shreyash Y W•
Jan 06, 2020
The week 1 and 2 were perfect, then week3,4 had some issues with the lectures- Andrew sir was repeating some parts and the problems/corrections in the slides.Also the week3 object detection was tough n the hints were not enough, with the errors in the assignment submission costing me a day
by Patrick C N•
Feb 02, 2020
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
by 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.
by 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.
by Richard S Z•
Apr 27, 2018
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.
Jun 26, 2018
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.
by Linying M•
Feb 22, 2018
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.
by 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.
by sambit m•
Jun 01, 2019
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.
by Max S•
Jan 12, 2018
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.
Mar 14, 2019
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??????
by Marco K•
Feb 17, 2018
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.
by 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.
by Oleg O•
May 22, 2020
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.
by Rosario C•
Jan 05, 2018
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 :)
by G C•
Mar 25, 2018
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.
by Victor P•
Nov 29, 2017
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.
by Sebastiano B•
Oct 21, 2019
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).