学生对 deeplearning.ai 提供的 Sequence Models 的评价和反馈

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.

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

Week 2 was wonderful to learn and understand. I wish to explore more on LSTM and Attention based models. Video lectures were not enough for me. Still I am happy for what I learnt.

Overall it is a good course. Much need to improve on the feedback of grading of which output is not really helping. Referring to global variables in assignments are really tricky.

Overall a very good course , i wish the model construction ( i.e. the rationale in stacking up the layers) is covered in bit more detail, otherwise an excellent course, no doubt.

The assignments can be made a little difficult. Can Include assignments of Image captioning, that would have been great. Overall a great course. Sir Andrew Ng, superb teaching!!

great course as always by andrew. would give it a 5/5 but had some sloppy mistakes regarding the formulas. overal impression : exceptional and highly recommended. thanks andrew!

Compared to the previous courses, this one was a little hard for me. Because Dr. Andrew tried to squeezed a bunch of information in this course. It's a wonderful course though.

Some of the assignments are very difficult to pass. I think I understand the concepts but the instructions for the assignments could be a lot clearer and provide more guidance.

I did not feel like I got a super clear understanding on how to use various library functions in keras, I did gain a really good understanding of the underlying models though!

Excellent content, although the exercises - at this stage of specialization - should focus more on NN architecture, than on pure computational and matrix slicing tasks, imho.