I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.
By Ktawut T•
Very useful materials for leading a ML research team
By Awalin S•
interesting insights about real world implementation
By Yu L•
would like to have more excercise related to coding
By Mage K•
Would've liked to have some programming assignments
Introduced a lot on engineering project experiences
By Marcelo A H•
Very interesting topics were shown in this course.
By William L•
Very useful knowledge that is not commonly taught.
By Alvaro G d P•
Interesting but perhaps we could have gone deeper.
By John H•
Is the flight simulator hw going to be added soon?
By Pat B•
Great course. I liked the compact, 2-week format.
By liu c•
A little bit abstract. But still very inspiring!
By Florian M•
Very interesting tools and ideas for applied ML.
By Jason G•
Not as strong as the other 4 of 5 of the series
Great course. Needs deeper practical examples.
By Francis J•
A lot of insights rather than technical details
By Lukáš L•
Coding exercises would be great in this course.
By Mares B•
A little short, maybe more hands on exercises?
By Ed G•
Concise course with some interesting concepts.
By Tulip T•
Quite helpful when you start a new ML project.
By S V R•
The session were simple, could be more complex
By Caique D S C•
very good course, could be less massive though
By Виницкий И В•
I want a program exercise like in 1-2 courses
By Dionysios S•
I would like to see more practice assessments
By Luis E R•
Very useful concepts that few people address
By Jun P•
Kind of boring than the cnn and rnn class ..