Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI
About the Course
Top reviews
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!).
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.
5101 - 5125 of 5,332 Reviews for Structuring Machine Learning Projects
By José G
•Lots of information, few knowledge
Change name to "Struc. Deep Learning Projects", all other forms of ML not considered, specially for P2.
By Eric K
•Too much similar material to the prior course, and only two simple quizzes, no hands-on programming assignments like in earlier courses.
By Eric M
•A fundamentally very good course with a few technical gltiches that can be easily corrected and some confusing elements to be clarified.
By Bongsang K
•I think this lecture is important for every research scientist. However, there was no programming examples so I was confused sometimes.
By 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.
By 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.
By Xiang L
•This session might not be very helpful for people from different backgrounds such as non-industral level application of deep learning.
By 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.
By Nitin S
•Decent learning. Though quite some stuff, I felt as repetitive and obvious.
I wish there was some programming exposure as well here
By 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.
By 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.
By Raghu t D
•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
By 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.
By Massimo A
•More theoretical than the other courses in the specialisation but still very high quality.
Short but with a lot of information.
By 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...
By 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.
By Shuai W
•The content of this course is a bit too little for me.
However, it provides useful guidance for my projects. Much appreciated!
By Gary S
•Not nearly as valuable as the first Deep Learning course. And the questions posed in the quizzes seemed far more subjective.
By Pejman M
•Programming practices with TensorFlow should have continued in this course. Unfortunately, these two weeks were all talking.
By Nithin V
•Need more quizzes, assignments to deepen the understanding, But otherwise thank you Andrew Ng for presenting this material
By Panos K
•The pace of the first part of the course was too slow. The second part (from Transfer learning onwards) was much better.
By Mustafa H
•This course does discuss interesting and important subjects but I feel it can be combined with course 2 of this series
By Ahmed A
•course is very good have a lot of important theory, it will be amazing if become 3 weeks with programming assignments.
By Kevin Q
•lot of issues with assignments and ambiguous quiz questions this time around, not as polished as other Andrew courses
Coursera Footer
