Great course for a beginner like me. I wish however that sizing of hidden layers/units should have been addressed as it is very difficult to achieve the optimum

Docked one star because of using Tensorflow 1.4 instead of 2.0. Docked another star because I found the course content less interesting than the first course.

Some of the videos are very abstract and needs a bit of mathematical intuitions. These intuitions are best obtained by calculations rather than a lecture :)

A bit too theoretical for my taste, lacks practical homework and getting our hands dirty. Really appreciated the final week's structure and topics.

ike usual andrew ng perfect explanation simple go to essential stuff.

the minus points some troubles with notebook

big thanks for andrew ng's team.

There are errors on some exercises (adam of week 2) still unsolved after over 1 year (found same error reported on the forum/discussion)

The lecture videos are good but the assignments are not that useful as they provide th answers within them and are somehow repetitive.

Lectures are good. Programming exercises are too easy. Too mechanical, no much thinking required, à la "fill the gaps" exercises.

I would give five starts if not for that grade error issue. I hope it gets resolved for good. Otherwise. Great course as usual.

Mostly good, last programming assignment had some issues with shapes required for various code sections not lining up properly

Interesting, but not nearly as good as the first one. Disjointed topics, unconnected exercises made this less digestable.

Decent class, but the last module(week) felt a bit rushed. Hopefully it was simply an introduction for the next class.

I think more should be done regarding the TensorFlow framework with more explanations given to what the functions did

Lake of practice, Lake of intimations with good examples

Less in Ternsorflow don't know how to implement and deploy it

The course and the material are great. However, the codes in the labs have serious problems which should be solved.

Really helpful advises. I felt it was too focus on the implementation side but I liked the intuitions parts better.

Week 3 of the course does not have a practice problem for batch normalization. Wanted to implement it and learn.

I found the video lectures useful to understand the concepts, but the programming exercises are over-simplified.

Not as good as the other courses in the specialization track. It seems there was a good amount of repetition.

Would give more stars if the final assignment used Tensorflow@ and not an outdated version that is not in use.

More tensorflow related tutorials should have been there. The lectures turned a little boring and redundant.

So far, I think this course is weak on theory, seems rushed and should provide more in depth lecture notes.

Encounter Error in the final assignment, cannot complete the model, but the grader gives 100/100 anyway.

Last programming assignment has an error due to which I cannot get more than 80% grade. Please Fix it!!

I wish the course mentors were more active on this course makes it a bit difficult to clear doubts