Jul 01, 2019
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.
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.
por Matthew J C•
Mar 28, 2018
The last course is in this series does not disappoint. I found this course to be more difficult than the others; likely because I had very little prior exposure to recurrent neural networks. However, this course is worth the effort as it opens up a realm of new possibilities; text, audio & time-series data. Whether you need to detect, classify or translate sequences, or even generate new sequences in the vein of some examples, this course is for you. There are several high-level APIs for performing these tasks but having a deeper understanding of what these APIs are doing is invaluable to your success. Take this course.
por Ricardo S•
Mar 04, 2018
An extremely well thought off and comprehensive introduction to sequence models, with examples taken from the most important/interesting application domains. Andrew NG's clarity of exposition is absolutely wonderful on such an otherwise complex area. The assignments are very cleverly chosen and helped me to finally get to grips with Keras. This being a new course, the assignment notebooks had a few minor issues that are well known by now and documented in forums and erratas, and will likely be fixed in subsequent reruns. Nevertheless, given the breadth and quality of the content, 5 starts are absolutely well deserved.
por Mehran M•
Jul 22, 2018
This was, in my opinion, the best of the 5 courses. Actually, here's how I'd rank the courses (from best to worse):
5, 1, 2, 3, 4
I learned a lot about sequence models and half-way through the course, I was able to jump right in and try some ideas I had in PyTorch.
The assignments could use a bit more work: I didn't really feel inspired by them and their "fill in the blank" style prevented me from thinking too hard.
All in all, I highly recommend this entire specialization. I was completely clueless about deep learning at the beginning, but now I'm actually trying out some novel ideas!
Thanks so much Andrew and the team.
por Rahul K•
Mar 19, 2018
This course, undoubtedly, has the toughest assignments compared to all the previous courses. The content is rich and informative. Again, pay close attention to the hints given in the programming exercises. If you don't follow, check the Discussion Forums to get a hint. Professor Andrew, your teaching is absolutely sublime - Crisp and concise. Personally, I would have loved an entire week dedicated to Attention Models as the entire concept seemed a bit rushed. Other than that, I have absolutely no qualms! For the people who are enrolling for THIS course only - make sure you're pretty good with Python and Keras.
por David R R•
Feb 20, 2018
Such a great course. It explains everything from scratch and teach you how to code in numpy (scratch) and how to code in keras to build high performance system (instead of tiny datasets).
I recommend this corse and the DeepLearning specialization as well. Thank you.
Es un curso muy bueno. En el se explica todo desde cero y te enseña como programar los modelos en Numpy (desde cero) o usando keras para crear modelos de alto rendimiento (a pesar de los datasets pequeños por falta de capacidad de computo).
Recomiendo este curso a todo el mundo asi como tambien las especializacion completa en DeepLearning. Gracias
May 01, 2018
This a the last and the most anticipated course for me. It's hard, informative and most useful. I've got chance to learn some popular and powerful methods within the years, like word embedding and attention mechanism. I start to understand the way deep learning community deal with NLP, i.e., ingenious design of network structure inspired by the pattern human beings perceive the world. It doesn't enjoy solid foundation as statistical learning does, but is works and suitable for engineering. That's astonishing! I hope I can combine deep learning with traditional methods to better understand NLP.
por Hu H•
Jan 03, 2019
Thanks very much for Andrew Ng and the other teachers, who made a series of these awesome classes including videos or programming works running on the jupyter-notebook. And also thanks the finical aid provided by the Coursera, I can't finished this course without your generous help. After a hard work with the Deep Learning classes, not only gained the knowledges, but inspired by the spirt from Andrew that "try to help people with your technology", which actually changed my mind, I will study more, do better to remember that in my life. Thank you and hope the world be a better place.
Feb 20, 2019
The last course is a little bit more difficult than the previous! Although I majored in Civil Engineering and got my Master's degree in 2018, since I finished the Machine Learning class of Ng 2 months ago,I found this art is so charming and powerful ,so I continued to finish the CS229, That is also a wonderful course!! And today,this DL course was also completed, now I am attending the CS231N class~ Thank you Ng ,thank u cousera, because of you,I have a chance to attend those amazing course from the most famous university. Ng,thanks,you are doing a great thing,thank u!!
por Solomon W•
Feb 12, 2018
Very frustrating grader. Really time wasting. What is this team trying to accomplish with such disorganized efforts? I hope to see more improvements in the future. I have just completed week1's assignments and revising my reviews from 1 to 4 because the course content is really good and has softened the disappointments caused by the grader.
After week1, the grader frustrations eased as it was working more and more consistently. Most importantly, I learned lots of cool stuff and so I am revising my reviews from 4 to 5. I hope all grader issues are now resolved.
por Florent G•
Jun 08, 2019
A huge thanks for this journey in the specialisation. The material is of high quality and the pedagogie of high qualiber! My only regret is that the course is not longer :P I would have love a course about GAN for example. Also an advanced followup on this specialisation would be amazing. Wanting to learn more i will probably continue my path with https://eu.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893?referrer=nvidia&utm_source=nvidia&utm_medium=partner&utm_campaign=referrerpage, however i would love to continue with deeplearning.ai !
por Marcel M•
Jul 27, 2018
This is a superb module which provides you with the skills that will enable you get going fast in developing real world applications that can be modeled as sequence data. You learn of the latest state of the art techniques of developing sequence models using techniques such as GRU's, LSTM's, how to debug them and also how to employ Attention models to make your models that much efficient for problems in NLP, Machine Translation and Speech Recognition. This course is a must for anyone who wants to be a sound practitioner of AI. I love it.
por Sikang B•
Apr 01, 2018
Though there are some minor lost clarifications in the flow, the general learning experience of this course is overwhelmingly practical and relevant to many real world scenarios. Personally felt this course completed the knowledge graph (of course I only have a preliminary understanding of everything) and opens many doors for future learning.
One nit-pick is Keras documentation can be annoying confusing and misleading at times. Would suggest to revise programming assignment instructions based on some popular threads in Forum discussions.
por Aleš D•
Mar 04, 2018
As usual, Andrew makes AI almost look easy. I have one comment about programming exercises. There are errors in the text sometimes and, at least personally, I don't have a habit to check discussion forums first, before starting work on the assignment so these things were sometimes a source of lost time, scratching my head where have I gone wrong only to find that the results are correct and it was the notebook that was not up to date.
This aside, I would recommend this course to anyone interested in AI. Keep up the good work!
por Ali S•
Jan 05, 2019
Finally, I understood LSTMs, thanks to this course, thanks to Andrew! Before this course, I spent many hours reading papers on LSTMs and trying to figure out what is going on with all these "Gates", but couldn't understand intuitions behind them. In this course not only I learned and understood them, but also I learned a lot about machine translation and speech recognition which I was frightened to approach them. This course gave me all fundamental concepts and tools that I needed to be able to deal with sequential data.
por Alina P•
Nov 23, 2018
Completed Deep Learning specialization in the DeepLearning.ie. I really liked this course, it will be useful not only for the beginners, but also for the specialists, which want to have an overview about current neural networks trends and see the interview from the best specialists of AI. To make this course perfect I would recommend to fix some errors in the theory of programming assignments (specially in the last 2 courses). Sometimes this issues are confusing and forcing to check on the forums correctness of the task.
por Kai-Peter M•
Oct 28, 2019
Great course!!! The best online course I have ever taken! I enjoyed almost every day I participated in that specialization, really an educational treasure! It is so comprehensive and detailed at the same time. Due to the good presentation of the topics it was really understandable. The only thing I would wish for future participants: please make it easier to get the complete Jupyter notebook environments from the Coursera platform once completed. I spent a lot of time here - even after consuming the related blogs.
por Tian Q•
Jan 06, 2019
Great content! Andrew's lectures are great as always. The assignments are absolutely exciting and fun. Obviously the team put a tremendous effort on the programming exercises to make them doable for laymen yet not trivial. The exercises avoid using libraries (like Keras and TensorFlow) at the very beginning. Instead, they started with the more basic Numpy implementations. After these practice, I am able to grasp what each layer is actually doing.
My only suggestion is to correct some trivial typos in the Notebook.
por James D M•
Feb 13, 2018
Thank you for helping me to get over the initial barrier to entry in NLP and audio data with this Sequence Models course. LSTM's are core to so many current technologies, and building them from scratch has provided me with good intuition for working with them. There was a good mix of numpy and Keras, as well as having the homework be clear enough to work through without getting stuck on minutia. It's always a pleasure to listen to Andrew Ng walk us through a problem with clarity, simplicity, and enthusiasm.
por Anders A•
Apr 04, 2019
The course is well thought and easy to follow. I regret not starting on this earlier in my quest to understand RNNs. It is the best source I found through shopping around. The courses is scheduled for three weeks, but is actually doable in an afternoon + a morning session if you have some python programming skills and enjoy 2x on your lectures. My one complaint is not with the course itself but the whole series. I mislike the subscription model for payments. I prefer a one time payment for life-time access.
por Maximiliano B•
Jan 02, 2020
In this last module of the specialization, you will learn in details how the recurrent neural networks works. I really enjoyed and had fun with the programing assignments specially the Emojify and the trigger word detection. After the course, you feel comfortable to read all papers mentioned as references throughout the course. Moreover, professor Andrew NG is awesome because he explains the content clearly, it is a pleasure to watch his videos and he provides everything you need to go the extra mile.
por tarun b•
Mar 03, 2018
Couldn't be more grateful for having the opportunity to take this specialization. The instructions were just at the right level of illustrating theory in practice, and the programming exercise at the right level to gain intuitions with implementation details. So many rights !!! Personally, I had the confidence that the syllabus is exhaustive and the callouts to research were just great. Overall ... excellent resource I will revisit often. Thank you to everyone who put this together and to Prof Ng.
por Vignesh S•
Oct 22, 2019
Thank you, everyone, on the team for such an orchestration of the course. It was excellent to get to know the concepts of deep learning and it increased my interest in the field exponentially. A special thanks to Dr. Andrew NG for those explanations given in detail. This course was really interesting and it definitely overturned my attitude towards NLP as at first, I thought this is gonna be a difficult field of AI.
PS: Keep that ever-smiling face of yours the same Andrew Sir. Thanks a lot.
por Amey N•
Dec 15, 2019
Smooth and hands-on walkthrough of basics of NLP and speech recognition. The flow of the course is very well-designed.
After having completed this specialization I can confidently say that I have a much better understanding of Deep Learning than what I had before I underwent the specialization. This includes the depth and breadth of DL, various models, their challenges, advantages & disadvantages, end-to-end pipelines, optimization techniques, background calculus & math, et cetera...
por Kuntal C•
Oct 20, 2018
This was my first AI course and I really made significant progress in my understanding of foundations of deep learning with this. Thanks to Professor Andrew's very informative course videos, grasping the complex concepts became possible. The quizzes and the assignments were challenging, made possible for me to use logic and develop new coding skills to go at it. I would recommend this course to everyone interested in AI/ML. Thanks to Professor Andrew for making this course.
por MOHD F•
Jul 23, 2019
This is an amazing course, it Provides a great Help...i have learned lots n lots of stuff about NLP, Learn about recurrent neural networks that work extremely well on temporal data, word vector representations and embedding layers --that are explained in a concise manner, and more importantly I love the Attention mechanism, the model that understand where it should focus...... its attention given a sequence of inputs.... amazing amazing ..highly Recommended.... Thankyou