good course, but unfortunately different with network and deeplearning course, that has fast response mentor. But all in all the course is full with knowledge

Excellent material! There was one error in the last assignment that cost me a lot of time. Please fix that. Otherwise, very useful programming assignments.

Very Good Course to understand Step by Step

Hyperparameter tuning, Regularization and Optimization to improve Deep Neuaral Networks & Practical Assignments !

Great course and great teacher. The skills in this course is very practical. But I think the assignment should use tensorflow version 2 instead of version 1

Learned a lot about tuning and different frameworks. Definitely math-intensive and more of a brief overview than a deep dive of these techniques and tools.

improving Deep Neural networks :Hyperparameter tuning,Regularization and optimization course was amazing! thank you so much coursera and Andrew Ng sir! :))

Similar focus should be given on programming assignments with a extensive discussion forums. Encourage learners to find functions themselves using google.

Please offer a lecture note in detail instead of just ppt shows for each class video, not to mention that some are missing which is inconvenient to recap.

Great material and lectures. Would've preferred slightly more comprehensive exercises though, and more on tensorflow(any deep learning framework) as well

The tensorflow programming assignment was a little too easy. It turned out to be more or less of a copy paste work without having to look at the TF docs.

Great intro to TensorFlow Framework. But the last programming assignment was still giving low percentage accuracy without any notable fault in the code.

The content was perfect but last programming assignment was excruciating! But I thank everyone involved in making this course, it was unbelievably good!

I feel like the second course was better then the first one. But there are a couple of typos in some assignments and the assignments are still too easy.

The intro of hyper parameters was from mathematical point of view as good as the basics of week 1, however practical relevance becomes not really clear.

As always - excellent lectures by Andrew Ng. However, I think that the programming assignments tend to be a it too easy and a bit too much "copy/paste".

Really enjoyed the course. Only suggestion is to talk about the programming side more in the lectures but overall I'm really happy Thank you very much.

In the last exercise of last week, we have to use TensorFlow v1 which was quite annoying if you already have learned tf v2 other than that great course

I wish prof. Ng provided more intuitions into underlying math particularly why gradient optimization techniques help. But like it anyways, very useful!

Great material, few minor errors that need fixing throughout. Noted in forums. I expect this will improve as more take the course and feedback applied.

Week 3 programming assignment required notions not touched in the training or mentioned in the instructions. Required lot of time to find information.

This course has to be updated!!!!! TF 2.0 is what we are using now, and especially for new users, it is important to start from the newest frameworks.

I missed in the course an explanation and possibly a programming assignment of different tuning algorithms, such as random search and Bayesian search.

The coverage on the subject was adequate but it will really help to make a pdf supporting document to highlight the hyper parameter tunning approach.

Probably a little too follow your nose at this point in the specialisation. But none-the-less very good. Would give 4.5 stars if that were an option.

Still some flaws + inaccuracies + video sequences that should be cut out. I think the organizers should really do it as people are now paying for it!