excellent course and very challenging!! The last programming assignment was a little frustrating having the correct answer and not getting credit for it until I changed the axis to None.

A great course with many simple code samples using tensorflow and Keras. The only issue was that instructors do not participate in the forums. Otherwise the content quality was excellent

Great course but in comparison with others of the specialization, the exercise did not leave that much as before.

Too focused on lines and not on the whole implementation of the ConvNet

The content is awesome, but using the old version of tf is not the best and obscures from the objective of either understanding the mechanics completely or creating CNNs with freedom.

Andrew Ng's simple explanation of complicated concepts lets you grasp concepts that require hour-long reading of research papers in a few minutes, Assignments could be more elaborate.

Der Kurs hat mir sehr geholfen und war Zeitlich gut zu schaffen.

Bei den Programmieraufgaben hätte ich mir ein paar beispiele gewünscht, um schneller in die Syntax einsteigen zu können.

It can be so much better if Andrew covers some more overviews. But it is still a great course and everyone should take it. Andrew gives the most understandable lessons about Yolo ones.

The first week was good and well presented. From the 2nd week onwards it as very cryptic. In the final week, on what are deep conv nets are learning, more details could have been given

I feel some of the theory was rushed here and high level functions used instead of explaining some of the more difficult concepts in the papers referenced, such as the Inception paper.

Good course, gives you a rough overview of popular CNN architectures and the basics of how they work. Assignments are easy but give you a chance to apply some of the stuff you learned.

The content was great, as usual, from Prof. Ng. But I wasted a lot of hours trying to make the programming assignment submissions, since auto save in IPython Notebooks kept on failing!

Minus one star for the assignment issue (triplet loss) for Week 4, this is a bit beyond acceptable considering how long the issue has evidently been there. Otherwise, stellar content.

Excellent content and explanations as usual. A small criticism for this course compared with the previous three is that the videos have clips of repeated content due to strange cuts.

Course content was good,but grader needs to be updated as in many cases I had to submit assignments manually by uploading it,as the grader wasn't working.Everything else was good. :)

Weird grader error on the week 4 assignment in triplet_loss function -- had to put axis=None instead of axis=-1, which is wrong (and contrary to the directions) -- needs to be fixed.

Great course. Very good and simple explanations of complex topics. The 4 is just for the sake I hoped for a deeper dive into Tensorflow and how everything changes with Tensorflow 2.

The problem with the triplet loss function and the grader was not solved until Dec 1st. This was misleading me, and, in order to grade fully I wrote a wrong version of the function.

A clear presentation of difficult problems and I love working with the notebooks. However meanwhile most of the tensorflow documentation hyperlinks within the notebooks are broken.

This course was of the same high quality and detail of the first three, but the last project was difficult due to bugs in the python code. This definitely needs to be fixed please.

The grader didn't work correctly on the final assignment. Course content was both really interesting and well explained though. Thanks very much for putting together these courses!

The content and lectures are still great. But the assignments and graders have a few bugs. I guess it's because of the insufficient preparing time. However, I did learn what I need

The lectures were excellent, but many of the exercises and quizzes had "issues" that wasted a lot of time. You need to spend a LOT of time on the internal forums for this course.

Great content and superb videos. The assignments are becoming exponentially more challenging if one is not familiar with Tensorflow as the intro on that framework is rather short.

great lectures.

yet there are some places to improve :

1) the assignment are harder (which could be good) yet they are hard by being less clear

2) there are some bugs in the grader