Content is good, but assignments are not interesting. Some application oriented assignments will be be encouraging.

Very good course, all relevant and well explained. I think it just needs and update for working with TensorFlow 2.

Like all other andrew ng courses this course is also the best course to deep dive into neural network algorithms .

I would like to see more programming assignments. They are very well done and it'd be great to have more of those.

I would really benefit from this course if more assignments are provided to try different data sets and scenarios.

Great course. Some guidance on implementing backpropagation with batch normalization would have been appreciated.

Absolutely love the course and the way Andrew teaches us, though I have a little bit discomfort in writing codes.

A little bit to theorical and with too many guidance at some points and not much at some other (for TF functions)

I liked the course, but the explanation of tensorflow needs more propaedeutic introduction for a learner like me.

Really helpful ! Too much concepts to understand but only applying few in the course. I really liked this course.

Good course to get familiar with hyperparameters and improving the neural networks. And cliff hanger was amazing!

Nice and practical. The assignments could go a step further in trying out different things to get better results.

Tensorflow exercise was not good , it could include some basics first. seems like only runnig it for no purpose

The contents are explicit and adequate but I think It would be better if I could get more exercise about coding.

It was great course, however, I would have liked it to be a lot slower with more time being spent on Tensorflow.

A great course!

I do feel that in order to become really good I now must apply the learned concepts myself soon.

Very well explained, but the Tenserflow explanation is shallow for those that have less programming experience.

This Course Helped me a lot in learning how to get best-optimized models by tuning Hypermeters.I really like it

A good course that provided more intuition on which models to work with and how to tune parameters effectively.

The Jupyter notebooks had a lot of mistakes which wasted a lot of my time otherwise the course content was good

Good lectures, but the jupyter notebook examples are inconsistent and sometimes use deprecated Tensorflow code.

I particularly benefited from the explanations of dropout, batch normalization and the RMSProp/Adam optimisers.

Many high level concepts are not explained in details so it felt quite difficult as a newbie in Deep learning.

Despite completing the course, I feel there is much more that I could be tested on to cement my understanding.

TensorFlow needs more time dedicated to it. I didn't completely understand the concepts behind this framework.