Grader in the last assignment is wrong. It has been reported in the discussion forums several months ago and still hasn't been. Apart from that, great content

The course gives you a good introduction to NN. However, the grading is buggy, and the content rather superficial. It gives you a false sense of achievement.

The homework assignments, compared to the other courses, where pretty low in quality. If these errors get corrected, I'd happily give this course 5/5 stars.

Videos were mostly great!

Expected more of the written material (quizes, assignments, etc.), not the quality I would expect from something I've paid for...

Some issues regarding the submission of assignments and some minute mistake in the videos and assignment. Although great teaching by Andrew as always :)

Issue with triplet loss function shouldn't happen. I had to remove "axis = -1" in order to pass grader even though function had produced wrong answer!!!

There are a lot of issues with programming assignments grader (I've spent one hour to complete assignment and two days to make a grader to get it)

The programming assignments contain bugs. Also the jupyter notebook kept on shutting down thus slowing down the learning process quite a bit :-(

Certain Parts are not that much clear. Specially like in the triplet loss function, until the coding was done the real procedure was not clear.

the assignment setup and graders are not updated after reporting issues several times which caused a great deal of frustration among students.

The last exercise it was a litle annoyng, it took me almost five days to figure out how to solve the face recognition because a grader fault.

I enjoyed the courses but I would like more practice, maybe a different module or examples aimed to help you define and optimize our models

There were repeats in the videos🤔 Also the answers to quizzes are not visible. If these would have existed, 5 stars would be reasonable.

Sometimes it was very difficult to understand lecturer because of his accent, but apart from that, assignments and lessons were helpful

This course is pretty good. Some things are not explained as well as Prof. Ng typically explains things, especially in the last week.

The Neural Style Transfer notebook seems to have makes it difficult in the last panel to access the generated_image global variable.

The assignments need to be reworked as they are quite confusing and the grading system is flawed especially for the last assignment.

More simple lectures with illustrations required and also graders need to fixed. Had a lot of time wasted because of buggy graders

It has very less explanation about working of back propagation of convolution network,

plus it can explain YOLO in much better way

The course is great but the assessments and grading is terrible, so many particularities and repetition that does not make sense.

Week 3, exercise 2 is very buggy. Couldn't have completed it without the discussion forum. Kindly fix it for the future learners

Found it really difficult to submit programming assignments, at times the jupyter notebooks were not at all responsive.....

Course content was good but lack with hands-on projects. It would be really helpful if the team could add capstone project.

There should be a way through which folks can download the entire zipped contents of the programming and also the lessons.

Very interesting and with high quality material. It could be improved by adding more tutorials about the frameworks used.