Jul 12, 2020
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
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.
By Asif I•
Dec 23, 2017
First of all, thank you for providing such a rich content.
I know its hard to strike a balance between covering content and "actually" delivering them to the student. Course #3 and especially #4 felt very rushed when it came to the exercises. The tensorflow concepts that came back out of nowhere and solutions would have been nearly impossible without the copious hints.
PS: Course 4 "happy house" face recognition assignment was choke full of bugs.
By nitin s•
Jul 01, 2020
Very good introduction to concepts on Convolution Networks. It would have been great to put more emphasis on how actual models like "FRmodel" are trained vs tested. E.g it would be great to provide information on the fact that 3 parallel networks need to be used that share weights. So more exposure to practical aspects of implementation would be useful. Essentially a lot more time can be spent on exercises than what is meant for them
By Michele T•
Apr 05, 2020
This was an interesting course. It provides a high level look at face recognition/verification and various state-of-the-art aspects of convolutional neural networks. The one thing I found frustrating in this course was the grader. It was very particular for at least one homework assignment on the order in which you entered your variables. I spent way too much time on debugging for simple things like that.
By Matthew C•
Jun 19, 2018
The content was great, and is probably the best available. However, the grader was so flaky it really shook my confidence in the material. I'm the type of person who will try and try until I'm literally about to give up before I look for help in the forums, so I lost a LOT of time on these exercises. This was by far the WORST of the five courses in the specialization. Sorry to yell, but YOU CAN DO BETTER!
By Alan S•
Nov 19, 2017
Depplearning.AI: Please do not release content unless it is ready. The content is fine, but the assignments were clearly hastily put together and had basic bugs discussed all over in the forums. In particular, week 4 is a complete mess. Boiler-plate code that doesn't even relate student-content (to load a dataset) doesn't even run for many people. This wastes everyone's time. Really disappointing.
By Bjorn E•
Nov 19, 2019
Overall a great intro to CNNs. But the last part of the course on object detection and facial recognition is very superficial. It explains the logistics of the disciplines (how to keep track of bounding boxes, etc), but it doesn't teach how to actually build such a system. The exercises make you fill in a bunch of indices and do vector math, but deliver the actual hard parts inside black boxes.
By Johannes 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.
By Emanuel D•
Sep 03, 2020
All video content of this course where great, but i can't say it about programing assignments. YOLO and Neural Style transfer are by my opion advanced topics. I would more appreciate longer programming excersice, not only something where i only add some piece of code and i hardly understand what is going about. For example, convnets were clear, i could implement it by myself, but yolo no.
By Santosh N•
Jan 03, 2018
Course lectures and questions are very good. The programming assignments are also good questions wise, but the grading mechanism is quite annoying. We had to find out clumsy workarounds to get the correct grading, in one case, the code change needed for getting the correct grade did not result in the expected output. Coursera needs to change the method of grading programming assignments.
By Jayson W•
Jan 26, 2019
I can't believe the number of technical problems I've had with notebooks not saving my work on homework assignments. It's very frustrating. The content is good and I will continue with the course, but this is the first Coursera course I've had (actually, the whole series in this topic) where I have experienced the lost of work - I just lost about an hour on a homework assignment.
By David C S•
Jul 16, 2020
I am very annoyed with the evaluation of the notebooks. Not with the content itself, but with the support from instructors, which is non existent.
It took me two days and 10 re-submitions to solve a problem that was unrelated to the code, but to the behavior of the grader system. No one replied my cries for help in the discussions.
Very disappointed with the lack of support.
By Stephen W•
Dec 08, 2017
The content of the course is very good, as with all the Andrew Ng / deeplearning.ai material. However production standards seem to have slipped for this one. Repeated sections in video material and a final notebook exercise that contained errors and required finding a work around that was posted in a discussion forum. I hope these things can be corrected for others.
By 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.
By Francesco B•
Apr 03, 2020
The content is very good. The exercises are a bit useless. Don' expect to be able to use tensorflow after this course. Furthermore, they teach the syntax of tensorflow 1 rather than the new 2. Therefore, when you try to solve the exercises you don't understand the discrepancies between the online documentations and what they want for these exercises
By Boyi Y•
Dec 05, 2018
Excellent course! I have learned the skills to combine image processing with machine learning.
However, the assignment of the Week 3 has a problem that you have not fixed for a long time, and thus it wasted some time. And the assignment in Week 4 has problems of submitting, and that's why I only rated three stars. Hope you can fix the problems soon.
By Ayush S•
May 17, 2020
The Face_recognition assignment was a tough one to solve, i only got grader problems but still i wasnt able to figure out how to pass grader even though my code yieded right answers. That's my only complaint otherwise the videos from Andrew were really easy to understand and the programming assignments were very well documented. Thanks :)
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 Christopher C•
Sep 09, 2020
Programming assignments were not to the level of the prior courses in the series. Should have more illustration of using Keras/Tensorflow. Assignments either were too spoon fed or there was too little reference information whereas prior courses had a good balance. Many of the keras links are dead.
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