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.
автор: José G•
Lots of information, few knowledge
Change name to "Struc. Deep Learning Projects", all other forms of ML not considered, specially for P2.
автор: Eric K•
Too much similar material to the prior course, and only two simple quizzes, no hands-on programming assignments like in earlier courses.
автор: Eric M•
A fundamentally very good course with a few technical gltiches that can be easily corrected and some confusing elements to be clarified.
автор: Bongsang K•
I think this lecture is important for every research scientist. However, there was no programming examples so I was confused sometimes.
автор: Michael L•
No programming assignments or labs, so too much theory, and too little chance to put same into practice. Not a good value for my money.
автор: Max S•
Still good but getting much sloppier. Bad editing of the videos, some exercises plain wrong and staff not reacting to forum posts, etc.
автор: Xiang L•
This session might not be very helpful for people from different backgrounds such as non-industral level application of deep learning.
автор: Lars L•
Course materials need some cleanup. Were a number of audio blips, in the video. Material was good but just didn't seem as polished.
автор: Nitin S•
Decent learning. Though quite some stuff, I felt as repetitive and obvious.
I wish there was some programming exposure as well here
автор: Taavi K•
Too short on its own (took half a day to go through the whole thing), could have been combined with Course 2 of the specialization.
автор: Jean-Michel P•
I feel like this course should be broken down and included in the other courses to get better context within these other courses.
автор: sai r t•
this session was good it would be more better if they provided the code of them..so that we could be abke to learn more from them
автор: Denys G•
Felt a bit rushed, each video was full of good tips but personally I think each video should have been a jupyternotebook instead.
автор: Massimo A•
More theoretical than the other courses in the specialisation but still very high quality.
Short but with a lot of information.
автор: David P•
Not nearly as good as the first two courses. These two weeks should probably be added into the second course at some point...
автор: Oliver O•
Would like more applied discussion and for it to be Longer. In particular I would like to see a discussion on class imbalance.
автор: Shuai W•
The content of this course is a bit too little for me.
However, it provides useful guidance for my projects. Much appreciated!
автор: Gary S•
Not nearly as valuable as the first Deep Learning course. And the questions posed in the quizzes seemed far more subjective.
автор: Pejman M•
Programming practices with TensorFlow should have continued in this course. Unfortunately, these two weeks were all talking.
автор: Nithin V•
Need more quizzes, assignments to deepen the understanding, But otherwise thank you Andrew Ng for presenting this material
автор: Panos K•
The pace of the first part of the course was too slow. The second part (from Transfer learning onwards) was much better.
автор: Mustafa H•
This course does discuss interesting and important subjects but I feel it can be combined with course 2 of this series
автор: Ahmed A•
course is very good have a lot of important theory, it will be amazing if become 3 weeks with programming assignments.
автор: Kevin Q•
lot of issues with assignments and ambiguous quiz questions this time around, not as polished as other Andrew courses
автор: Arghya R•
Could have more case studies and above all. Also programing assignments on self driving car could have been better