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.
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.
By Rodrigo N S•
Outstanding course, but the end of it uses many architectures not fully explained (GRU and such). Incredible course and specialization, though!
By Reda M•
Excellent course, but I would have liked to work on predictive maintenance examples leveraging RNN and LSTM networks. Big thanks to whole team.
By Nishant B•
The course is nicely designed and every topic is explained in a very lucid manner by Andrew Ng. Must be done as a beginner in sequence models.
By Suraj S J•
Simplified content delivered in just the right way to give a perfect intuition of the complex concepts. Really enjoyed doing the whole course.
By Harry T•
Great content, but Andrew often starts his phrases then restarts saying them. Audio could use some cleanup, then this course would be perfect!
By Yunhua J•
Most optional assignments contain bugs/errors. Other than that, this is a great course, just as the 4 other courses in this specialist series.
I give 4 star because some fomulas are not correct! Though this course is really great. I can not understand why you made mistakes on fomulas.
By Rohit T•
This one seemed to go through to quickly over the details especially with the word vectors and the LSTM, would have appreciated more examples
By Joris D•
Very good course, though the assignments towards the end were a little too centered around Keras, which I personally don't care for very much
By Leung P L•
The instruction of using Keras in the programming assignment is unclear. There are many bugs as well, hence we have versions 1, 2 and 3 etc.
By Ruben Y Q•
No time series analysis, and some problems in the guidance of some programming tasks. Mainly de first week, the rest of it was pretty good.
By Jean-Michel C•
Good course. I would suggest to split the first week into 2 weeks, which makes easier to grasp all the concept with a deeper understanding.
By YU Y•
The assignments of this course "Sequence Models" require sufficient knowledge of Keras and Tensorflow, which is not friendly to beginners.
By Dongliang L•
There are some problems in the code of the assignments, as well as the expected outputs, which costs a lot of time for me to figure out.
By Ahmed N•
Very Awesome Course i got knowledge about Sequence to Sequence models and how they works in practical software . Thanks to Prof.Andrew.
By Filippo V•
Exercises' grader didn't accept all the functions correctly, lose much time searching in the discussion.
Too many corrections in the way
By Heinz D•
Great instructor, good and challenging assignments. Thank you!
The grader problem in the Dinosaur Island should be solved once for all.
By Chuanxiao X•
Everything is great except the last assignment - trigger word detection is hard to save and submit, and i can't even open it sometime.
By Tommy S•
Parts of the critical details are a little vague, but the intuition and experience provided are extremely valuable and useful for me!
By Nisar S•
Found it a bit harder to follow along. I believe this topic needs a more indepth treatment and possibly more time (4 weeks at least).
By Niklas V•
Really good course, but the audio quality (repetitions, periods of silence etc) was decreasing over the course of the specialization
By Allan C M•
The exercises are somewhat tough for this exercise I think the time should be extended by one week extra to complete the assignment.
By Jinfeng X•
The material is great. On the other hand, if we could get a lecture on Keras, it would help us work on the programming assignments.
By Marvin J A•
Besides some technical difficulties in the notebook (and some minor details in the video quality) the course was very informative!
By Alexander T•
Overall well executed course and sequence. You'll pick up RNN essentials and use Keras/Tensorflow to work through simple examples.