AV
Jul 11, 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
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.
By Reyrey
•Mar 17, 2018
Sometimes it was very difficult to understand lecturer because of his accent, but apart from that, assignments and lessons were helpful
By Stephen D
•Mar 17, 2018
This course is pretty good. Some things are not explained as well as Prof. Ng typically explains things, especially in the last week.
By Carol S
•Jul 19, 2020
The Neural Style Transfer notebook seems to have makes it difficult in the last panel to access the generated_image global variable.
By Jkernec
•Jan 12, 2018
The assignments need to be reworked as they are quite confusing and the grading system is flawed especially for the last assignment.
By Jnana R D
•Mar 13, 2019
More simple lectures with illustrations required and also graders need to fixed. Had a lot of time wasted because of buggy graders
By VORA N
•Jun 11, 2020
It has very less explanation about working of back propagation of convolution network,
plus it can explain YOLO in much better way
By 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.
By Sudhanshu D
•Apr 8, 2018
Week 3, exercise 2 is very buggy. Couldn't have completed it without the discussion forum. Kindly fix it for the future learners
By Ankit R
•Oct 7, 2019
Found it really difficult to submit programming assignments, at times the jupyter notebooks were not at all responsive.....
By Gowdhaman S
•Apr 22, 2018
Course content was good but lack with hands-on projects. It would be really helpful if the team could add capstone project.
By vishwanathan r
•Nov 15, 2017
There should be a way through which folks can download the entire zipped contents of the programming and also the lessons.
By Carmine M
•Apr 12, 2018
Very interesting and with high quality material. It could be improved by adding more tutorials about the frameworks used.
By Corbin C
•Jun 1, 2018
Poorly edited videos, poorly worded (bordering incorrect) quiz questions, buggy notebook. Good, useful content, though.
By Bence K
•Jan 29, 2020
The content of the course was perfect. But the support for the issues and the feedback for the forum threads is awful.
By Siarhei K
•Mar 28, 2018
For the YOLO part would be nice to have explanation for how to set up training set and train your own object detector.
By junchen f
•Dec 31, 2019
The homework portion of CNN is underwhelming. We are asked to play around the core algorithm but not the core itself.
By Claudio T
•Jan 14, 2018
The content of the course is a lot of fun. I loved this module. But unfortunately the grade engine wasn't work right.
By Martin N
•Mar 17, 2019
The exercises are awkward - it is a lot of index juggling and I feel it does not help me understanding the "whys".
By Aditya M
•Jun 21, 2020
The audio was not clear ( mostly was of low volume) at moments when the instructor was telling important points.
By Michal S
•Apr 5, 2020
some videos weren't properly edited (repeated sentences).
I like the assignments but the machine was too slow.
By Rajib C
•Mar 31, 2019
The Algorithms should have been touched in depth, so that we could learn and apply everything from scratch.
By James H
•Dec 30, 2018
Great intro to CNNs - would be 5 star but downloading the support files to your own machine is such a pain.
By Tatsunari W
•Mar 28, 2018
A great introductory course in CNN
A little too many hints and too much guidance on every coding assignment
By Ajeet M
•Oct 7, 2020
I would like for the course to be a little bit more difficult as far as writing the programming exercises.
By Ritvik A
•Aug 30, 2020
End of the course was not well structured. But the starting of the course was good and very well planned.