Oct 29, 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.
Jun 30, 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.
By Dunitt M•
Apr 26, 2020
Recomiendo ampliamente este curso, te proporciona un claro entendimiento de los modelos secuenciales y recurrentes. Es excelente, aunque a diferencia de otros cursos de esta especialización no explicaron en detalle algunos aspectos de las RNN, me hubiese gustado que profundizaran un poco más en backpropagation.
By chandrashekar r•
Feb 6, 2019
The RNN, LSTM< and GRU were very good. But the Week 3seemed a bit abstract. More could have been covered in Audio, Attention.
ALso the Jupyter Notebooks was frequently crashing, and it took lot of attempts to re-open the existing one. Lot of time wasted. Also it took long time to to submit and run the program
By Eysteinn F•
May 27, 2018
This course provided a nice high level overview of RNN models and associated Keras implementations. The tricks and tips given were a useful addition to my ML arsenal. The only thing that I feel discredits this course is that the programming assignments are easy to gloss over and pass without much engagement.
By Bill T•
Mar 19, 2018
Great introduction to RNNs and how to implement them in keras. I suspect it is a relatively new course as there are still typos and a few errors in the assignments (otherwise I would have given 5 stars) but the forums help you to find your way around them and hopefully in future versions they will be fixed.
By Amir T•
Dec 5, 2019
Excellent lectures, some part was difficult and it took time for me to imagine the content of each parameter (e.g. when we talk about X, or a, or Waa what is the size of them and what do they represent). But in the exercises, it became more understandable. Exercises need previous knowledge of Keras and OOP.
By Shuxiao C•
Feb 5, 2018
It is a fabulous course content-wise. However, I personally find the programming exercises overly easy (the instructors already build the framework for you and the only thing you need to do is to fill in the blanks), s.t. I'm still not able to build an RNN from scratch after completing all those exercises.
By Tien H D•
Jul 10, 2018
This course is good. It introduces the concepts regarding recurrent models. I specially like the attention model videos. In general, the exercises are well written. However, I'm not very familiar with Keras and working on the Keras code really takes my time even I'm quite experienced with Tensorflow.
By Ting C•
Jul 20, 2018
Professor Ng did a good job explaining sequence model and I finally understand the basic theories. However, there is room to improve especially on the Keras library part. I hope you can add some simple tutorial for that. Also, I still don't understand how to translate the architecture to Keras code.
By Vijeta D•
May 4, 2020
This is a very well structured course. I initially started this course almost 10 months ago but got distracted and started to learn sequence models on my own. But, at the end end I resorted to this course again and got my basics cleared out. Thanks to deeplearning.ai team for designing this course!
By Alberto H•
Feb 23, 2018
Great explanations on the videos, and well designed programming exercises. However, the complexity of the programming tasks is not well dimensioned (1h - 1:30 h may be too little). Worse, some of the exercises are not well explained, with misleading information (e.g. about model tensor dimensions).
By K173664 S K•
Nov 4, 2020
this is a well structured course, but it is not for beginners at all, andrew ng had put alot of his efforts in this. As a computer science major, I was able to grasp the maths concepts but for anyone comming from diffrent background its far from possible to understand all the theoratical concepts.
By Pedro H B D•
Aug 30, 2019
There was not enough theory as the first three courses. Some explanations were superficial and difficult to understand. Maybe drawing the shape of the inputs, outputs, and other matrices in lectures would help to better visualize what's going on inside the networks. Overall, it was a great course.
By Miguel S•
Nov 27, 2019
It's a great course. The information and knowledge that you get about Sequence Models is fantastic as a primer. Andrew is an amazing teacher throughout the entire specialization altough I found the content of the videos in the Sequence Models slightly more rushed than the previous 4 courses...
By Daan v d M•
Nov 16, 2020
The theory was absolutely interesting and an eye-opener. The programming exercises were hard to make because of the keras/tensorflow knowledge and I actually ended up just fill-in in things, as were given in the examples, without really knowing what I was doing. Time for a Tensorflow course.
By Thiago H M•
Apr 18, 2019
Poderia dar um pouco mais de instruções na hora de usar as funções do Keras. Ficou um pouco confuso.
No assignment da semana 3 (Machine translation). Tem um output que não precisa estar exatamente igual mas o curso não fala isso e acabei gastando bastante tempo nisso, só vi depois no fórum.
By Sujay B•
Apr 9, 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.
By Juan S C•
May 9, 2022
I Love it! every single part of the course!
The reason I give it 4 stars is to get the attention of the developers and lecturers of the course.
Please, please, please improve the customer service of coursera. Please give the site deeplearning.ai more support from lecturers and people experts.
By 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.
By 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 :).
By 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.
By David G•
Jan 3, 2022
Assignment for week 4 offered little instruction. The exercises for implementing the np.newaxis for the get_angles instruction is not sufficient. The link for the np api as well does not include np.newaxis in its library. This assignment while very useful was disproportionately difficult.
By Ali B•
Sep 1, 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.
By Chenyue W•
Feb 8, 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 :)
By Lukas K•
Sep 3, 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.
By Seyyed M A D•
Mar 6, 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