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.
Very good. I have no complaints. I though instruction was very clear. Assignments were very helpful and challenging enough that I learned something, but not so challenging that I got stuck too often.
por Aliaksandr P•
This is a very interesting topic. However, I believe the course itself can be improved. I believe there can be more information about NLP and sequence models in lectures. It would be nice to add lectures with practical suggestions about training and tuning sequence models. There were lots of typos and mistakes in notebooks that were found by other fellow students and not addressed by mentors.
por Heyang W•
The course overall isn't as good as the previous 4 ones especially for the PA part, I can pass the grader even with wrong output. The PA improvement sometimes just create more discrepancy. The PA is just a walk through of how to building those basis models, but those little bugs will drain extra hours to figure out. I think this course is kind of a prototype one especially on PA part.
por Peter F•
Compared to the previous courses, this was a disappointment. There is not as much content as I expected and the homework exercises are not well prepared. If one spends more time with debugging than with "learning concepts" in a basic course like this, then something seems wrong.
Moreover, in a situation where so many people pay so much money (because of Andrew Ng's credit)...
por Vivek G•
That was tough, how the weights are stored and their dimensions inside the 'time steps' can be explained by adding one more video, btw the course is awesome if you want to learn the basics of sequence models, you should have completed the previous 4 courses before diving into this. I will always remain thankful to Andrew Ng for providing this type of platform.
por Odinn W•
Positives : Excellent lecture material. Assignments broadly are well structured. HIgh bar set by Andrew Ng. Negatives: Assignments have too many errors and mistakes as of Jan 2019 (especially but not only in the optional / ungraded sections) for me to be confortable 100% recommending the course. Instructions for assignments are also not fully fleshed out.
por Sumandeep B•
This course is good for introduction to sequence networks, but I felt this is not at par with the previous course 4 (CNN). This feels a bit hurriedly done, with many important things only just touched upon. This should have been a 4 week course like the previous module. Then due attention could have been given to the field of speech, audio, sequence domain.
por Krzysztof J•
The course is generally good. However there are some issues with lecture videos editing (some sentences are said multiple times), and with activities (e.g. default settings hardcoded in one of notebooks, didn't let have output shown as reference, also in some cases automated grader has some assumptions, which need to be found using trial and error method).
por Cristian M V V•
Great course, great activities and really good programming excercises.
I give it 3 stars because instructors let political views tainted week 3 videos and assignments of this course by introducing some techniques for 'debiasing' and making your neural networks more bias to gender equality political views. That has nothing to do with science.
por Jerome B•
I've got mixed feelings about the whole Specialization. Many very interesting topics, but on the other hands I don't feel like there's any takeaway knowledge for me. Until the very end I've been feeling completely lost in the exercices. I'm proud to have been able to hold on until the end but I'm not sure it's been an useful use of my time.
por Aditya B•
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.
por Miguel O•
It´s a fairly good course, with lots of cool topics covered on it. My main complain would be that the subjects covered are dense enough to be arranged on a four or even five week course. Instead, for some reason, all the stuff has been squeezed within three weeks, which makes the lectures shallow and rather cryptic most of the time.
por Romain L•
The course was great, as ever. But some of the programming exercises were very frustrating. Oscillating from very easy to very difficult, with some unclear (and sometimes erroneous) instructions. I felt this was in sharp contrast with the previous 4 courses of this specialisation, for which the course and exercises were perfect.
the course covered a lot of essentials and gave me a rough idea of how stuff NLP and sequence models work. Though at the same time the content often left me confused and overwhelmed. the Convolutional Networks course was far better.
Overall its great work and I am thankful for hard work put behind the complete specialization.
por Hans E•
Great lectures, great teacher!
I would have given 5 stars but for the problems in the exercises / grader. Some problems that are know for weeks or even months are not resolved. This causes many wasted hours for many hundreds of students. Please solve this and make it a 5 star course.
Many thanks to Andrew Ng and the mentors!
por Glukhov E•
The programming tasks were very simple. I doubt that you can really learn anything when you just need to copy the text from the task description and paste it. The content of the tasks was excellent, but the level of personal involvement was minimal.
In addition, the information in the course is already outdated.
por Richard S Z•
The lectures were OK ... better LSTM tutorial by Chris Olah
The exercises really need some review ... very frustrating ... and not all that illuminating .
The course was a good intro to DNN ... but I think either replace Week 3 - Structuring ML Projects with a course on Keras ... or add a course just on Keras.
In my oppinion this course was too hard. I mean I could solve the assignments, but there was too much "magic" in those assignments. At least for me it was hard to develop enough intuition. But maybe its also due to the fact that I am more interessted in image based convnets where I have more background.
por Piotr D•
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.
por Suresh D•
I guess as the subject matter becomes more complex, more training is required on the underlying frameworks being used- Keras, TensorFlow etc. Did not feel that sufficient time was spent on understanding the underlying frameworks. Also the TA work is of spotty quality. But I love the way Andrew teaches.
por Salih T A•
The assignments were not good i think. Because they explained the consepts too long and complicated as like we've never seen these on lectures. I was waiting assignment to require more insight about architecture and less python programming knowledge. This comment is for week1 assignments in special.
por Christopher C•
Programming assignments were not to the level of the prior courses in the series. Should have more illustration of using Keras/Tensorflow. Assignments either were too spoon fed or there was too little reference information whereas prior courses had a good balance. Many of the keras links are dead.
por Devin F•
For me, there was a large gap on time between when course 4 and 5 were offered (months). This unfortunately was enough for me to forget everything I learned about Keras.
Of course, this course assumes you know Keras so I was behind for the labs
Material is interesting though.
Of the courses in the specialization, this one seemed the least organized and rushed. Some of the assignments had some annoying auto-grader quirks that made troubleshooting a pain. Overall it is still worthwhile, just be ready to search forums for help during the assignments.
por Kerry D•
Too many thing introduced in programming assignments without explanation. Why the high dropout values? Why sometimes one dropout layer, sometimes two? Many things are just given as a formula, and not explained in a way that would let me make my own network for my own problem.
por Alessandro P•
The lessons are very good as always, but I'd like to be tested more in the programming exercises rather than literally being told what to do and then fill in missing parts of already completed code. Still super glad I took the specialisation, it has been extremely helpful.