Nov 23, 2017
I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
Jul 02, 2020
While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).
por Daniel K•
Jun 25, 2020
This time it was not that well-structured than the previous courses. I thought we would learn how to structure step by step an ML project.
por José G•
Apr 19, 2020
Lots of information, few knowledge
Change name to "Struc. Deep Learning Projects", all other forms of ML not considered, specially for P2.
por Eric K•
Jul 21, 2018
Too much similar material to the prior course, and only two simple quizzes, no hands-on programming assignments like in earlier courses.
por Eric M•
Oct 20, 2017
A fundamentally very good course with a few technical gltiches that can be easily corrected and some confusing elements to be clarified.
por Bongsang K•
May 21, 2018
I think this lecture is important for every research scientist. However, there was no programming examples so I was confused sometimes.
por Michael L•
May 02, 2018
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.
por Max S•
Dec 13, 2017
Still good but getting much sloppier. Bad editing of the videos, some exercises plain wrong and staff not reacting to forum posts, etc.
por Lars L•
Dec 30, 2017
Course materials need some cleanup. Were a number of audio blips, in the video. Material was good but just didn't seem as polished.
por nitin s•
Jun 25, 2020
Decent learning. Though quite some stuff, I felt as repetitive and obvious.
I wish there was some programming exposure as well here
por Taavi K•
Nov 30, 2017
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.
por sai r t•
Aug 06, 2018
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
por Dennis G•
Nov 24, 2017
Felt a bit rushed, each video was full of good tips but personally I think each video should have been a jupyternotebook instead.
por Massimo A•
Nov 18, 2017
More theoretical than the other courses in the specialisation but still very high quality.
Short but with a lot of information.
por David P•
Oct 17, 2017
Not nearly as good as the first two courses. These two weeks should probably be added into the second course at some point...
por Oliver O•
Oct 16, 2017
Would like more applied discussion and for it to be Longer. In particular I would like to see a discussion on class imbalance.
por Shuai W•
Sep 19, 2017
The content of this course is a bit too little for me.
However, it provides useful guidance for my projects. Much appreciated!
por Gary S•
Sep 16, 2017
Not nearly as valuable as the first Deep Learning course. And the questions posed in the quizzes seemed far more subjective.
por Pejman M•
Oct 21, 2017
Programming practices with TensorFlow should have continued in this course. Unfortunately, these two weeks were all talking.
por Mustafa H•
Jul 17, 2018
This course does discuss interesting and important subjects but I feel it can be combined with course 2 of this series
por Ahmed A•
Jul 10, 2018
course is very good have a lot of important theory, it will be amazing if become 3 weeks with programming assignments.
por Kevin Q•
Mar 19, 2018
lot of issues with assignments and ambiguous quiz questions this time around, not as polished as other Andrew courses
por Arghya R•
Sep 19, 2017
Could have more case studies and above all. Also programing assignments on self driving car could have been better
por Okhtay A•
Apr 06, 2020
A bit too free form compared to the other courses in deep learning specialization, but maybe that was the goal.
por Masih B•
Jul 18, 2020
This course could be way more better, if it also focused on codeing with tensorflow (like the previous course)