The material itself is very informative and useful. But I have to give "just" 4 stars because, the training videos have to be edited better and there were a few mistakes in the programing exercises.

Please work on getting the notebooks to work properly. Also very bummed that after canceling my subscription, I won't have access to my homeworks. You guys should give us lifelong access - we paid!

Could have been more polished like the earlier courses in the deep learning specialization. Particularly the programming exercises could have benefitted from more comments like in earlier courses.

A general overview into the power of sequence models. There is no rigorous mathematics here so most of what students can learn is high-level implementation and intuition about the various models.

Es el mas complejo de todos los cursos de la certificación, faltna alguna traducciones que lo hacen un poco mas dificil de entender algunos conceptos, pero leyendo y probando se logra entender.

Great final module !

General feedback : was expecting an application example other than image, speech recognition such as related to Supply chain management, production planning, pricing etc.

An appropriate course for getting started with Recurrent Neural Networks and its very applications in the domains of speech recognition, sentiment classification, neural machine translation etc

Overall teaching of Andrew Ng sir is Fabulous, but it was very hectic with the technical problem of the last assignment and I would like to thank Andrew Ng sir for the teaching me this course

Very useful materials, but a little hard to digest. It will be more helpful if course lectures and slides can dive a little deeper into each model and provide more granular technical details.

Exercises are sometimes vague and can be done without full understanding of the material. No officially given notes. No reading material that explains the concepts more clearly and in detail.

One of the best course i ever taken. glad to be part of such wonderful course teach by prof.andrew ng. learn a lot about sequence model and NLP. Highly Highly recommended for beginner in NLP

Great Course, very insightful excercises, really enjoyed it - unfortunately some issues with the programming excercises.

Since it's the first run of the course they should have fixed it soon.

the course content was really impressive, but some topics need to be explained in detail. Also working of LSTM should be further described in detail. Programming assignments are really fun.

great course, lots of implementation details that are important were glossed over, while other areas had too much hw hand-holding + strict requirements on what the code needed to look like.

Its a very good overview. I feel the last course somehow took a big jump and became a bit hard, because one module is not enough. It makes sense, that there is an extra NLP specialisation.

Very glad I took this course! A little rough around the edges as far as video / assignment quality, but seeing that this is the very first run of this course, I know it will only improve.

The material was great. Some of the programming assignments ramped up in difficulty or lack of perfect execution. However, I still gained extremely valuable information from this course.

The lecture for Sequence model was good motivation to get interesting about text and audio processing. All of lectures were very fundamental and intuitive. Thank you very much. Prof. Ng.

Very good and fun course in the sequence. However, it would be very nice if there were some examples of using RNN for things such as self driving etc, outside the realm of speech and NLP

The course videos are very good. However the optional parts of assignments have lots of issues and errors. Please update the assignment to reduce the time wasted unnecessarily debugging.

Very interesting exercice and assignments from which a lot is to learn. Content quite complicated which will require from me to come back for review and deepen some points. Thank you !

It was necessary to study extensively the Keras framework to fulfill the code tasks. I suggest an extra module with small simple RNN modeling exercises to better adapt the framework.

Overall, I really like this module. One possible improvement might be providing more information for backpropagation. Maybe as an optional video or just reading materials. Thank you.

nice course even few chapters could be more detailled technically speaking. However the assignements are very nice and helps to complete the understanding. Many thanks for such work

Thank you Andrew Ng for making me comfortable with the deep learning topics on Sequential data...Assessments were interesting ..can be made to enable us better play with the models