The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.
I was really happy because I could learn deep learning from Andrew Ng.\n\nThe lectures were fantastic and amazing.\n\nI was able to catch really important concepts of sequence models.\n\nThanks a lot!
por Sebastian S•
The ideas presented here were clear, however I found the programming assignments non-intuitive and not practical. I spent on them way more time than I wish i had.
por Fernando A G•
I enjoyed all the courses, from my personal point of view this course was not that fun as the other courses. Except for the trigger assignment it was awesome!
por Zhao H•
Too much was given in external python code for the first week's assignment (that should be learnt by us): not a good thing for us to gain a good understanding
por Matias A•
Worst course of the specialization, content is interesting and Andrew keeps explaining really well but programming assignments are clearly of a lower quality
por Max W•
The course is great but the tasks in Keras are too complex without background knowledge. Therefore, a reasonable introduction in Keras would be desirable.
por Eymard P•
Far less detailed than the other ones. The programming assignements are less interesting too, as a great part of the work consist of reading documentation
por Reetu H•
There were lot of bugs in the assignments taking up lot of time to fix. The course was okay, I liked the other courses in the specialization more.
por Kaupo V•
The Keras programming exercises are quite weak. Please re-think how to teach them more systematically. Currently it is quite a lot of hit and miss.
por Assa E•
That was much harder than the previous courses of the specialization. However it felt like the videos are more hasty and less understoodable
por Leandro A•
There was a bug in a programming assignment notebook that took too much time to notice that i was doing ok but the expected ouptut was wrong
por David H P•
The programming assignments required some extra effort to understand Keras which I thought may need an introduction video like tensorflow.
por Iván V P•
Several grader issues, only 3 weeks of work, and a lot of errors in the solutions... In addition, less content than in the other courses...
por Rishabh G•
The earlier courses were easy to understand, however, this was way too difficult. Andrew Ng did not make this easy like the other courses.
por H Y•
Compared with previous courses, this one seems to be rushed. The focus on applications seems to be much higher than the theoretic side.
por Yash R S•
Not as great as the other courses in the specialisation. The assignments can be a little off putting, but lectures are top class again.
por Roberto S•
Week 1 took double time to be completed. Times proposed for the assingnement are underestimated.
Please readjust the assingement time.
por Ankit S•
Assignments are not up t the mark.. Expected to have high vocabulary size word embedding assignment, Machine Translation assignments
por Nachiketa M•
This course was good but in comparison to the other courses in the deeplearning course series, this course lacked adequate depth.
The course is a good course because the lecture Ng.W ,but the exercises is not easy for our beginers for such tools like kears.
por Seng P T P P•
The programming assignments in this course are difficult to implement. The detail descriptions are needed inside the notebooks.
por Thomas N•
Good subject, but a lot of the course material (like lecture slides and problem sets) was either unavailable or out of date.
por Vinjosh V•
The videos are great - however it would be useful to provide some help on how to implement the concepts programatically.
por Søren M•
Not as good as the previous courses in the series, and some of the assignments where broken, and super hard to debug.
por Laurent B•
Only on NLP applications, it would have been great to apply GRU or LSTM on numerical data like finance for example.
por Devansh K•
The content covered is interesting, but I feel like the explanations are not as intuitive as the previous 4 courses