Oct 30, 2018
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.
Jul 01, 2019
The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.
von Daniel E•
Jul 12, 2018
I believe that the course needs more time allocated to the incremental teaching of this rather large subject area with varied applications. Just needs to be a better way.
von Ankit S•
Jul 17, 2018
Assignments are not up t the mark.. Expected to have high vocabulary size word embedding assignment, Machine Translation assignments
von Xueying L•
Jul 22, 2018
Too narrow focusing on applications in NLP
von CARLOS G G•
Jul 26, 2018
von Fernando A G•
Jul 27, 2018
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!
von Luca B•
Jul 27, 2018
A nice course after all, but I expected something more. It is valuable if you know nothing about RNN and NLP, or if you know something and want to go a little deeper and work on some guided keras examples.
What it is not, is an in depth RNN course. It's very short: in my case the 3 weeks boiled down to 2.5 fulltime days. Not enough for a full review of the topic.
Homeworks are interesting but:
-very simple, no large scale application
-short rounds of CPU training: no GPU, no access to server clusters
-keras layers are used without much explanation about it, this is sad since keras docs is really incomplete about usage examples. I'm referring to calling an LSTM layer inside a loop to manually create all the timestep stucture!
-keras layers are used that have never been introduced in the course (such as BatchNormalization)
-often heuristics for network topology and hyperparameter values are not clearly explained, leaving the student with no insights on how to approach different tasks
von José A M•
Aug 05, 2018
Too many stability issues on the platform to get the notebook up and running.
Few bugs and errors on lectures and exercises, if they are found by the community you should update the material even if it involves recording a video again. Too much time spent on the notebooks figuring out "side" stuff that is not what I am here to learn.
While on the course for CNN it covered the state of the art of the field, in LSTM I think there is much more that could have been explained.
I have missed examples on other type of problems like forecasting time series, events and other more business like applications.
Still I learnt a lot and would do it again.
von Joshua P J•
Aug 01, 2018
The material provides a strong overview of sample problems for which sequence models work well. However, the class doesn't give users the conceptual mastery needed to apply sequence models to new or related problems. The issue is that the motivation and concepts underlying new architectures aren't well-explained (they're often an afterthought at the end of a lecture). This approach to teaching feels backwards.
Specific issues: Week 2 & 3 homework treats lecture material as mostly black boxes so they aren't particularly illustrative. The week 3 Attention Model lectures make no sense, are taught in reverse order, and feel unfocused (with apologies, I know there's a bad pun there; it's not intentional). In Week 3, I ended up skipping to the homework because I found lecture exasperating; to my surprise, the Markdown comment boxes in the Python notebooks explained the material better than lecture did.
von Max W•
Sep 07, 2018
The course is great but the tasks in Keras are too complex without background knowledge. Therefore, a reasonable introduction in Keras would be desirable.
von Yao G•
Sep 12, 2018
The assignments should be improved. More prep on Keras will help improve the efficiency of learning.
von Mason C•
Sep 12, 2018
Had to rate this lower due to problem with the final assignment. Submission and saving situation was a nightmare, I had to redo my work several times. Please fix this, it's a real downer at the end of the course. Otherwise, content stellar as always.
von Ashvin L•
Oct 22, 2018
The course content is pretty good for breadth. However, it falls short in going into depth. Assignments need to be more open-ended and probably a bit more involved. It appears that we are cutting and pasting code that is already written in comments.
von Michael K•
Aug 06, 2018
Assignments are very buggy and instructions misleading or incomplete. However the core material is excellent
von Hang Y•
Aug 24, 2018
Compared with previous courses, this one seems to be rushed. The focus on applications seems to be much higher than the theoretic side.
von Noam S•
Oct 27, 2018
The lectures were not as good as the previous andrew ng. courses, and the exercises were quite bad in all honesty.
I do appreciate what I have learned, as the lectures WERE clear enough.
von Piotr D•
Nov 17, 2018
The course does not explain how to use Keras (it's assumed you've finished the previous course). What's more a lot of code parts is implemented in some difficult way (for loops instead of Python's builtins and idioms like any or list comprehensions). I'd love to see more materials on speech recognition.
von Travis J•
Nov 25, 2018
The subject matter was a good introduction to various RNN model types and concepts. I have to dock a couple stars, however, as the course leans so heavily on Keras implementations during the assignments that it really should be listed as a firm requirement. While I feel that I'm more experienced with both RNN models and the use of Keras now, it was a struggle with what felt like a lot of cargo culting for me to get through most of the assignments. I don't consider the brief lesson on Keras at the end of the second course to be sufficient training, particularly if much time has passed between taking that course and this one. A brief "Lesson 0" on Keras is sorely needed at the beginning of this course. Otherwise, it should be explicitly and firmly communicated at the start that the programming assignments require a certain familiarity with the Keras framework. Overall, I do highly recommend this course, but be forewarned about the need to be familiar with Keras before starting.
von André T D S•
Oct 02, 2018
Bugs in the programming assignments grading kills the flow
von Eymard P•
Jul 31, 2018
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
von Aditya B•
May 09, 2019
Really interesting course with fascinating applications. However, in terms of difficulty, it is a significant step up from all the previous courses. A lot of time is spent figuring out the syntax even though the concepts are crystal clear. ( Probably as it is a collaboration with NVIDIA). The programming assignments could be improved.
Apr 26, 2019
Esperaba que los ejemplos fueran de otra forma
von Bradly M•
Apr 17, 2019
The scope of this course was highly relevant to me, but unfortunately many of the class materials were broken or otherwise incorrect, making some ungraded portions of the assignments difficult or impossible to achieve. Activity on the discussion boards indicates many people have tripped over this for at least the better part of a year, but no corrections have been made. This was quite frustrating and wasted a good amount of my time.
Apr 19, 2019
Works as a primer. Assignments aren't that great.
von Gaetan J d B•
Jun 17, 2019
fairly more complex and deeper as previous courses. Nice ex. however.
von Gautam D•
Jun 17, 2019
To be completely honest, I loved Dr. Andrew's method of teaching. But the assignments just flew over my head because I didn't have enough hours of practice of Keras under my belt. I know Keras is there to make things easy but it's very difficult to just trying to pass the grader. To goal of assignments was fantastic, I mean, generating music, etc. sounds really amazing but I feel that if there was some more time given to make us better in Keras and other technicalities then I would've loved this course much more!