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.
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.
need to teach us more about tensorflow to do last week's assignments
by Alex K•
Good content but the Coursera homework platform is severely broken.
by Iván I•
The videos are not properly edited. Exercises are not very useful.
by Kshitij S•
A bit difficult than prior courses. Still, enjoyed learning. :)
by Himanshu A•
The convolution operator seemed a bit abrupt in the first week.
by Adriano C•
There are many things to improve in the programming assignment
by Dong Z•
Not very clear, still need to learn a lot to understand CNN.
The FaceNet assignment is bugged as hell! Please fix it ASAP
by Srijan G•
The programming difficulty suddenly increased exponentially
by Michał Ł•
Very nice course, but grader issues kill all the pleasure.
by Yiyun Z•
The the Yolo assignment, the IOU part has grading problem!
by Jonathan B•
Good content but assignment grading has lots of problems!
by Andrea L G•
Nice introduction. TensorFlow part can be improved a lot
by Shuo C•
Great course but lots of bugs in assignments and videos.
by aman g•
Programing assignments were more life fill in the blanks
by Xin H•
Some of the details are not very good just like yolo.
by André T D S•
Bugs in the programming assignments kills the flow.
by STEFANO F P•
Too easy excercises and with an old version of tf
by Fengjun W•
I hate the errors in the assignments and graders
by Gleb F•
Too much emphasis on python programming skills.
by Guglielmo F•
The Neural Style Net sheet has to be reviewed!!
by Tze-Yuan C•
The coding assignment is a little bit too brief
by Antoine H•
Several bugs in the last programming assignment
by Maciej G•
too much material related to vision detection
by Han K K•
Too much technical errors in the assignments