Mar 14, 2018
I was really happy because I could learn deep learning from Andrew Ng.\n\nThe lectures were fantastic and amazing.\n\nI was able to catch really important concepts of sequence models.\n\nThanks a lot!
Oct 30, 2018
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 Sam D•
Feb 25, 2019
Awesome course and specialization. Now, to implement everything I learned in my own programs, and of course I will be sure to revisit the videos until everything becomes second nature. Learn, program, improve and repeat. Thanks!
By Himanshu G•
Apr 26, 2020
This was particularly intensive course of this whole series, learned a lot.
Thanks to Prof. Andrew NG, accept a Natmastak Pranam from this Student of yours, will always be indebted for what I have learned here. You are the Best
By Rahi A•
Jan 09, 2020
I have many of books and blogs related to RNN, but was not clear and confident about it. And after studying only the first week video and lectures, I am so confident and happy that cant tell you!!! Thank you so much Andrew...;)
By leonardo d•
Dec 05, 2019
It seems like there are several and very useful RNN models. Many of them are very good at specific tasks, and if you take this course you will be abe to understand and implement many of them. It was a really amazing experience.
By Sandeep P•
Jun 27, 2018
An excellent introduction to the theory and practice on recurrent deep neural networks. Great usage of all the 4 courses in this series to culminate with this course as a great finish to deep learning theory and implementation.
By Rafael E•
Feb 11, 2018
Yet another amazing class! I'm so grateful for the existence of these classes. It makes mastering deep learning very much easier. My thanks to Andrew, and all others who have worked so hard to make this course possible! :-)
By Hristo B•
Feb 25, 2019
Most notably, an exercise guides one through the building of a recurrent network from scratch. More exercises show the value of different architectures and make the learner proficient in using neural network libraries (Keras).
By Aparna D•
Oct 30, 2018
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.
By Jeffrey T•
Apr 02, 2020
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.
By Dmitry N•
Oct 06, 2019
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.
By Gopi P V R•
Mar 16, 2019
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.
By Nick S•
Mar 30, 2018
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.
Jun 05, 2020
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.
By Seungbum H•
Jun 03, 2020
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.
By Salman A•
Apr 23, 2020
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.
Jan 22, 2020
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.
By Moses W W•
Nov 03, 2018
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!
By BA M•
Apr 25, 2018
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.
By Sorin G•
Apr 21, 2020
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.
By Junfei S•
Dec 10, 2018
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.
By TATSUYA T•
Aug 26, 2018
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.
By Joakim P H•
Aug 20, 2018
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.
By Shankar G•
Jul 13, 2018
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.
By Michal K•
Mar 14, 2018
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.
By Rúben G•
Nov 02, 2019
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.