Course it good, but IMHO to simple.

BTW I do not have real experience with NN.

It would be beneficial to give more details on how tensorflow optimizers work

This is an important course to go through for improving deep neural networks.

Very nice one. Focus on practical aspects that are quite necessary to use NNs

too complicated, many lessens in couple of short videos.

poor video transcript

Se podría mejorar mucho la redacción del libro del ejercicio de programación.

more python / tensorflow, as well as data exploration and cleaning is welcome

Very good. The only downside is the reliance on an old version of Tensorflow

Excellent on the basis. could cite frameworks like hyperopt, hyperas, etc...

There are still some minor typos to correct, but it's a great course anyway!

Builds really well. Didn't know about gradient checking before this course!

activity at the end used tensorflow 1, support for tf2 would be appreciated

Programming assignments can be made more rigorous with more hands-on coding

everything is good, jypyter notebooks are slow gets confused in assignments

I really liked it because it made me specially under stable with Tensorflow

Great, but could be better. Fix the typos. Add summarized video notes. Etc.

The Last assignment on Tensorflow can be improved and explained in detail.

The Tensorflow part was hard. Pleas add more explaination to the notebook.

Pls update to Tensorflow 2.0. Its a bit discouraging to learn and unlearn.

Insights about how machine learning works in real life is quite ingeniuos.

very good lecure.

somewhat difficult to me. I will repeat again and again.

Very informative but got some issues with the last programming assignment.

More rigorous independent projects/assignments are needed for this course.

Deepened my understanding of how to make deep neural networks work better!

very extensive content. I missed more text content to support the theory.