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.
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.
创建者 Serkan Ö•
I dont understand why notebooks are become unavailable when I am working on it. It says method not allowed and then please login through www.coursera.org. Then I had to run all the cells again. I think this is because of the lack of resources like # of servers available. Other than that, like the content of the programming assignments. Especially the trigger word detection algorithm worked perfect with my own voice, that was satisfying of course.
创建者 Betiana F•
This course is a great introduction to sequence models and a great way of finishing the specialization. All main areas were covered. It is a good entry point for those who want to keep improving their sequence-models skills.
Keep in mind that Keras is needed (not a basic level). In comparison with the other courses, the exercises here sometimes are more focused on the preprocessing that in the model itself. Nevertheless, more than recommended.
创建者 Erik B•
I got an overview of how people use this technology but the whole network architecture and especially dimensioning remains to be somewhat of a black art.
The overview is much better then one could obtain by downloading tools, or reading framework-centric books. It provides also a lot of information through the references to the scientific literature.
It is clear that this is a field still in its infancy but the results are already amazing.
创建者 Sandeep J•
Awesome course. It feels like this one was more rushed than the others in the Specialization. I am a bit concerned whether the "Specialization" has become a "Survey" of the course, and leans heavily on the assignments for teaching..but then, could do more for why some architectures are the way they are. The assignments improved from being a spoon-feeding exercise. That's good. But, on the other side, Keras documentation was confusing.
创建者 Zhisen C•
The 5th course materials were not as solid as the previous 4 courses. Mainly due to heavily use of Keras API and lack of Numpy implementation. There is nothing to complain about indeed as for the same amount of content the 5th courses had covered, implementing on Numpy will take way longer. Maybe adding more explanation on how the Keras API work will help a tons. Overall it is a very good course that I would recommend anyone to enroll.
创建者 Aditya T•
Excellent series of courses! Loved the lectures and thoroughly enjoyed the exercises! A big thanks to Andrew Ng and all the instructors and mentors. The forums provided useful hints on the couple of occasions I was stuck. While I would have initially suggested providing more info on Keras APIs, in hindsite the additional time spent in searching Keras documentation was useful arriving at better understanding of the infrastructure.
创建者 Aditya C•
The Literature for RNN's was not motivating enough compared to Convolutional Networks and the previous courses. However, Andrew did concentrate on the important aspects which would help us in building RNN ourselves. I did feel the assignments were not as elaborative and extensive as the CNN's but I understand the idea behind it (being just to make users aware of the skeleton of the model instead of doing everything from scratch).
创建者 Peter G•
This one is much better then the previous one - Coursera team definitely made their homework. However some theoretical blank-spaces are still left. For instance - nothing is said about how recursive gates are being updated during BPTT backward pass. For someone who has the some experience and read some other sources that is not a big deal, but for a complete first-timer who pays attention and uses his brain - this is a pure flaw.
创建者 Stephen R•
Very interesting application of deep learning. Gives a good overview. Assignments are fun, yet it's too easy to complete the assignments without understanding the big picture. I found the "attitude" assignment in week 3 a bit difficult to grasp however. Particularly liked the dinosaur names, emojify, the humour and positivity in the course: mentioning gender/racial bias, encouraging people to do good with their skills. Namaste!
创建者 Dave J•
Very good overall. Andrew Ng explains the material clearly and accessibly.
I'm deducting a star for occasional issues that get picked up by volunteer moderators on forums, who do a great job, but seem not to get corrected by Coursera staff. Also for one or two small inconsistencies in terminology between lectures and programming exercises. However I've seen much worse and more confusing inconsistencies in other courses.
创建者 Ankush K•
I thought the course and the specialization was great for people who want to get into the details of deep learning. Although I enjoyed learning about all the details, I wish there was a separate course specifically for Keras and TensorFlow. In practice, we will rarely have to implement the models from scratch, and having a better understanding of Keras and TensorFlow would be more helpful in terms of career prospects.
创建者 Eli C•
Andrew has a very good video-lecture style.
The programming exercises can be a bit frustrating at times for the wrong reasons, but at this point the course has been available long enough that you should be able to find a thread in the Discussion forum that provides enough hints to resolve any issue you might encounter. Nonetheless I appreciate the effort that went into designing the programming assignments.
创建者 Damian S•
Presentation is amazing... Professor Ng always does fantastic job of communicating the material in a clear and easily understood way.
I took the course on the first run-through, and there were still some kinks in the grading process that were a little frustrating to deal with, but hopefully these will be ironed out for later versions.
Thank you, Professor Ng, and everyone else involved. You never disappoint!!
创建者 Michael D•
This course has excellent content. Unfortunately there seems to be a slight drop in quality compared to the other courses in this series, with respect to the programming assignments. I didn't find them to be very clearly explained or illuminating.
I'd recommend the jupyter notebooks be reworked with better explanations and more attention to the notational conventions.
Still an excellent introduction though.
创建者 Jeff B•
The lectures were outstanding (as usual), but the programming assignments (except for the final Trigger Word assignment) were terrible. I spent almost all my time trying to figure out Keras syntax, without ever having a Keras tutorial or anything. If you are going to rely on Keras, you should probably add a tutorial or some references. A lot of wasted time. But other than that, this course was amazing.
创建者 Ishwarya M•
Very good course. I liked the speech recognition part more. I found the assignments involving Keras code difficult to do in both RNN and CNN courses. Without the help of discussion forum i wouldn't have completed the Keras assignments. Thank you all the fellow students and mentors for your contributions to the discussion forum. Thank you so much Andrew and team for putting this awesome specialization :)
创建者 Ivana S•
As the other courses in this series, this is definitely another great course, and explains to details the various sequence models. I gave it 4 stars because I believe it might need some improvements. Compared to the previous courses it felt a little rushed, and had too much new information and long programming exercises for a single week. Maybe it would have been better if it was 4 weeks instead of 3.
创建者 Cristina B•
Always a great course but I would expect to have more lessons on how to use Keras and Tensor Flow API in a better way for who needs to use them in real NLP applications. I still have some doubts on how to use them correctly (for example the use of time distributed layer in the last exercise 'trigger word detection' that we didn't use in the architecture for the exercise about attention mechanism)
创建者 David C•
I really enjoyed this course and learned a lot. The descriptions of GRUs and LSTMs were a little scant, however, and I found myself rewatching the videos trying to get my head around them. The course could be improved by going into a little more detail about the different gates and what it means to train them, or what sorts of information or patterns might be relevant for the training of a gate.
创建者 Daniel C•
Although I loved the course and learnt a lot, I don't feel as confident trying to implement some sort of sequence modelling in practice compared to the other courses. And yet I still got full marks for this section. I think the course could have been spread out to 4 weeks with a few extra examples (maybe some stock market prediction examples). Regardless, thank you so much for the teachings!
创建者 Lida G•
I really enjoyed learning this course and gained a lot of knowledge from it. The only challenge that I found was some of the steps of the assignments were not clear. I could resolve them by checking the forum. I would also like to know more about document summary and document similarity, but there was not much content for it. Overall, thanks a lot for putting this valuable content together.
创建者 Anatoly R•
Great material and amazing Andrew Ng (5 stars) but very pure editoral review (videos with a lot of repeats of canceled phrases, pauses, quiz understanding, grader problems, very poorness of mentors support because they can do nothing to help, neither contact deeplearning.ai, in summary it's looks like alpha version of course not release and diserve 3 or even 2 stars), so in total 4 stars.
创建者 Vikram R•
This course is almost as good as the prior four, but some of the lectures lack detail, there are mistakes in some quizzes, and the programming assignments at times are crammed too full of information. You can end up passing through this class without really understanding what's going on, whereas the CNN class does a much better job of forcing you to understand things before you pass.
创建者 Daniel Z•
Excellent lecture content.
Some of the programming assignments are quite poor. Sometimes there are minor mistakes in function descriptions, and other times the whole assignment architecture/plan is not well thought out. If the staff doesn't have resources to improve this, then allow the community to create branches and submit merge requests :)
Overall, I'm happy with this course.
创建者 Paulo V•
The lectures were great, making an advanced subject accessible. The course materials were mostly good -- the exception being the optional (non-graded) assignment in Week 1, which was not well-structured, and failed to reinforce the concepts it was intended to. There were challenges with connectivity to the Jupyter notebook server, which caused much frustration and wasted time.