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.
von Sujay B•
Apr 09, 2018
Though the lessons are interesting and mathematically demanding, I felt that it was a good time spent learning these concepts. Overall I feel that the 3 weeks could be split into 4 weeks and learning could have been much smoother by adding some more lessons to address the contents of Week 2.
von Anna C•
Jun 23, 2019
Nice content, but the assignments are too easy and only demonstrate the pipeline instead of providing hand-on experience in picking the network and training with GPU. Also, there are some grader problems which has wasted my time to make my code pass the grader even if the answer is correct.
von Jingbo L•
Mar 16, 2018
The homework grading methods need improvement. I got the right model and get the right results, but still have to spend tons of time to make the submission pass the grading system. It is a waste of time for future learning. You may want to train a DL model to solve this grading problem :).
von Richard M•
Oct 25, 2020
Great explanation of theory (RNNs etc.) and easy to follow course structure. The programming exercises are disappointing though: They mostly consist of mindlessly copying Keras functions without an understandable (!) explanation. Many provided links to the Keras documentation are outdated.
von Ali B•
Sep 01, 2019
Obviously, The professor and TAs have put a lot of time for preparation of this course, and I really appreciate it. However, the hws of the course is too much focused on language translation. They could put another examples, say business data, to represent other applications of RNN/LSTMs.
von Chenyue W•
Feb 08, 2019
The course should provide more instruction on the Keras and Tensorflow, since the notebook is largely dependent on the knowledge of these frameworks. Moreover, the logic of programming is not so well-organized: I personally prefer to have my own logic instead of modules got implemented :)
von Lukas K•
Sep 03, 2018
Really interesting course with overview about sequence models and what can you do with them. Lectures from prof. NG are amazing as usual. The only thing I was missing was maybe more tutorials on Keras LSTM usage. The exercises on LSTM were quite confusing, especially using shared layers.
von Seyyed M A D•
Mar 06, 2020
Very Important !!!
We do need more programming assignments in order to master the material. We joined Andrew's courses to master (not just get introduced to) the materials, because Andrew and the rest of the team is awesome.
Thank you very very much for all your time and consideration
von Faraz H•
Mar 13, 2019
I am overwhelmed by too much material. Additionally Tensorflow and Keras syntax is not very elegant or coherent as they are such high-level languages. I learnt a lot at a high-level overview in this course, but my fundamental understanding was consolidated in the previous 4 courses.
Sep 08, 2019
Finally, the last course was completed. For me, this course is very difficult, because the content of the course is somewhat obscure and difficult to understand. But I learned some basic knowledge about Natural Language Processing and Speech Recognition through this course. Thanks!
von Carolina F•
Jan 08, 2020
This is my third course in Deep Learning, the contents and pace of learning are great, they provide a good level of understanding in the subject. The notebooks have bugs and I wasted a lot of times making them work, thus they could be improved to use that time actually learning.
von Osman F K•
Dec 24, 2019
The concepts presented in this course were advanced enough. Yet, the assignments did not require much effort and thinking, which in my opinion is hurting the learning process. If students do not struggle enough with the course, they tend to forget the material they have learned.
von Othman B•
Feb 22, 2018
Very interesting courses. I take this as a basis for future applications. I only regret that the exercises are too guided. I can't pretend to be able to accomplish a project in machine learning :-(
I would recommend also to note all the references to the papers, they are helpful.
von Cosmin D•
Sep 26, 2018
Great content, assignments are fun and reasonably instructive (although they contain the occasional error and the video editing for the lecture content seems a bit rushed at times). I would recommend this course as an introduction to recurrent neural networks and related ideas.
von Justin G V P•
Apr 19, 2020
Very informative and well taught course on sequence models. The amount of content and pacing was just right as not to be overwhelmingly complicated. There are a few bugs here and there in the programming exercise which can lead to a lot of headaches but overall a good course!
von Sergei S•
Aug 19, 2020
Great course, with interesting programming assignments, but still, I couldn't catch intuition about GRU and LSTM nature (I understood its pupuse and equations but couldn't get why exactly THAT combination of equations is necessary to allow RNN learn long term dependencies).
von Mikhail M•
Jun 12, 2018
Week 3: quite a complected network was used for trigger word detection; however, it is not clear why exactly this architecture was used; specific order of dropout, batchnorm and GRU seems to be a pure magic; at least, a few words why this combination is picked are needed.
von Elena J•
Sep 28, 2020
very good hands-on course. Yet I wished in the programming assignments, it was stated clearer, whether the implemented code is for understanding purposes only (and hence being the reason to be implemented) or is still mandatory even when working within a library (keras).
von Stephen S•
Feb 17, 2018
Course content is excellent, I would have given 5 stars, if the Programming assignments wouldn't have bugs. Fortunately people in forum help out with solving issues with assignments. I believe it's due to the short time frame the course is online and bugs get corrected.
von Viliam R•
Mar 24, 2018
While this was the most relevant course for me, I missed how it was focused on "helper functions" instead of core RNN concepts. While I feel like I understand concepts like the Bleu score, I would definitely need to spend more time to fully grasp the RNN architecture.
von Jeff M•
Oct 04, 2020
Very nicely put together, takes a difficult topic and gives you just enough to get your head around it. Only thing keeping it from 5 stars is that a few times it was more difficult to figure out what the auto grader wanted than what was needed to complete the topic
Jan 24, 2019
Would have been nice to get more extensive training in Keras en Tensorflow because programming excercies were somewhat too pre-compiled at times or other times difficult to code because of scarse knowledge of these packets. Otherwise great lecture material as usual
von Vidar I•
Mar 22, 2018
This was a great course and teaches you everything you need to know about RNN to get started doing your own research. With background in economics and finance it would have been nice to have one small assignment with time series data. Beside that, awesome course :)
von Sourish D•
May 28, 2018
The grader has some bug.Even with correct output and with no bug in the code, it gives incorrect grading. Firstly the criteria to pass is so stiff(80% means to pass for every function).Secondly the bug in grading function grades incorrect for correct codes.
von Sherif M•
May 03, 2019
Andrew Ng does a great job in introducing Sequence models in this course. However, I have the feeling the theory behind all the concepts falls short. There are just too many different subtopics being covered instead of focusing on the main concepts of RNNs.