My one critique is that the TensorFlow topic was suddenly introduced.

course is not updates to tensorflow 2 but overall it is very helpful.

Suggestion of references, as a complement, would be very interesting.

Content needs update to leverage the state of the art in the subject.

It's a hard course but the materials are great and their explanations

Needs more real coding exercises taht aren't mainly just copy & paste

generally good but hope to get more assignment about parameter tuning

Course was insightful but seemed difficult to grasp at some moments.

Tough Concepts are not explained clearly like dropout regularization

Not as much detail on the topics as the first specialization course.

Learnt a lot, assignments not as complex as would have hoped though.

Material are excellent, but some assignments have little bit issues.

Batch norm concept isn't taught well. Otherwise the course is good.

I liked it, but the tensorflow introduction came to early I think..

There can be little more clarity in the Batch normalization topic.

Informative course, last exercise could be updated to Tensorflow 2

Grader is not performing well even though my outputs are matching.

Lecture were quite good. But the course assignments were too easy.

By itself, not really a couse. It should be part of the first one.

few mistakes in course assignment but overall good course material

The programming assignments were too easy, otherwise good content.

A good course. I get familiar with the idea about hyperparameter.

I would have liked to have more practice exercises about tunning.

good course but there are some small bugs in video and exercises.

Goes bit into nity grity, which would be required in the future.