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.

Should update the last lab to use the latest version of tensorflow (TFII)

Would have been more helpful if TensorFlow was covered in greater detail.

Practices are more like "type after me" than a real learning opportunity.

Excelent course with very interesting insigth on tuning a multilayer ANN.

Great course. The tensor flow introduction part could have been better.

this course will help me to improve my academic skill beside help future