This was quite a tough one.. But it was almost magical when the outputs of the assignment were successfully completed. Excellent. The discussion forums helped a lot, as the instructions were not very clear to novices like me.

Great explanation of hard material, still wish there were more assignments, and they were more complicated and less guided, or start with simple assignment and increase the complexity and eliminate the guidance in next ones.

Amazing course, Andrew Ng presents the material in a concise and intuitive manner. It would be nice to have access to all of the material needed to fool around with the assignments on our computers in an offline environment.

Thank you for this wonderful sequence of courses! This whole concept is still a bit blurry for me, but as a lot of people during the interview have mentioned, one must simply exercise new skills to understand the technology.

It's great course to get concepts right and overview. It will be great if you add further programming assignments(other than partially coded ones) or resources as such where one can practice what he had learned as optional.

Great choice of material, i would be happy to have one more week of that course to see more examples and have more time to familiarise with the concepts. All weeks were very useful and all the material was greatly explained.

I enjoyed all the courses of the specialization but I was looking forward to Sequence Models the most. I think a lot has been covered in this course and I can't wait to try working on projects with the knowledge I now have.

This course is good , I learn RNN,LSTM,GRU etc.Just one thing, the last assignment is hard to submit.I guess maybe there is a systematic problem that need to be solved. Everything except that is great. Thanks a lot, Andrew.

This is an excellent course for a beginner like myself. I would like to thank Andrew for making this course available to everybody in the world. Thank you so much for your inspiring course. With best regards, Seungbum Hong.

This course has helped me in developing an understanding for implementing sequence models through Recurrent Neural Networks that can be used in number of applications such as Natural Language Processing and Audio detection.

A briefly introduction of Sequence Models to solve sequence problem, such as translation, speech reorganization..etc. Homework is also very helpful to understand what is going on step by step under Recurrent Neural Network.

This is an excellence training course! I had a wonderful experience learning the leading edge Artificial Intelligence knowledge specialized with Deep Learning and believe this will make a life-long impact to my career path!

This Specialization is flawless. Yet I wish C5 W4, Transformer assignment, had more explanations, didn't have a couple of bugs, and had a cell for inference time experience with the model. All in All, 99 out of 100. Thanks

Excellent Course! The maths and concepts were a bit tough to understand and I had to look up some(a lot) of stuff but the learning experience and the thrill of actualling building and training the model is very satisfying

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My favorite by far, and I'm not a fan on NLP. Sequence Models, especially attention mechanisms seem to have so much potential. Interested in using them to look at time series data analytics for industrial iot applications.

Excellent Course by Professor Andrew NG, I enjoyed learning what lays under the concept of Deep Learning and Neural Networks.

Thank you very much to Andrew Bg and the team, and as well the mentors supporting the students.

The course content is great overall! The only thing I am a little unhappy is that one or two of the programming exercises have confusion instructions. But finally I made it under the help of peers on the discussion forum.

One of the best courses in this specilazation. Programming assignments are so creative and fun :). Shout out to the creators!!!. If anybody want to learn about NLP and Transformer Networks, then this is the right place.

RNN model was quite difficult for me to learn, but all these lecture videos and programming assignments helped me understand it better. I liked the "Trigger word detection" (the last assignment of this course) very much.

Absolutely fantastic course! Perfectly follows on from the Machine Learning course by Prof Ng et al.

(One slight issue with some videos' audio: there was a very high-pitch whistling that was almost painful to the ear.)

At first I thought this was the least interesting course, but after the lectures and labs I have to say that this is really the most interesting of them all. However it requires some knowledge from the previous courses.

The final course was very brief and bit harder to digest. The assignments and quiz where also tricky but, overall had fun. Thanks Andrew Ng and team for the Deep Learning Specialization course to be offered on Coursera.

Out of all five specialization courses, this was second most useful (right after first course in the series). Also one of the few that used any modern DL framework (Keras) and not implementing pseudo solutions in numpy.

I was able to understand the difference between sequence models and previous course models. Moreover, I understood now how text and speech can be processed by AI. Finally, I could understand better the Keras framework.

Stunning attention (pun intended) by Professor Andrew in explaining delicate details of the inner workings of neural architectures, and very nicely designed programming exercises to make every week's content hit home.