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.
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.
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 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 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 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
By Arghya R•
Could have more case studies and above all. Also programing assignments on self driving car could have been better
By Okhtay A•
A bit too free form compared to the other courses in deep learning specialization, but maybe that was the goal.
By Masih B•
This course could be way more better, if it also focused on codeing with tensorflow (like the previous course)
By Janet C•
Overview of the machine learning process. No projects or sample code to actually organize the ideas into code.
By Aniruddh B•
Very nice, but I don't believe the content merits a full course. It could be integrated with courses 1 and 2.
To much talk but understandable. Need something like programming examples with different data distributions.