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.
創建者 Kerry D•
Too many thing introduced in programming assignments without explanation. Why the high dropout values? Why sometimes one dropout layer, sometimes two? Many things are just given as a formula, and not explained in a way that would let me make my own network for my own problem.
創建者 Alessandro P•
The lessons are very good as always, but I'd like to be tested more in the programming exercises rather than literally being told what to do and then fill in missing parts of already completed code. Still super glad I took the specialisation, it has been extremely helpful.
創建者 Mason C•
Had to rate this lower due to problem with the final assignment. Submission and saving situation was a nightmare, I had to redo my work several times. Please fix this, it's a real downer at the end of the course. Otherwise, content stellar as always.
創建者 Ashvin L•
The course content is pretty good for breadth. However, it falls short in going into depth. Assignments need to be more open-ended and probably a bit more involved. It appears that we are cutting and pasting code that is already written in comments.
創建者 Oliverio J S J•
This course presents an interesting review of several strategies that are part of the state of the art. However, it is impossible to assimilate how they work in the time devoted to each one. The "fill in the blanks" exercises do not help much.
創建者 Jorge B S•
This course gives a nice overview of sequence models. If it is true that I do not have an engineering background, I felt it got sometimes a little bit too abstract as compared to other courses of the specialisation. However, I recommend it.
創建者 arnno b•
I would advise giving more tutorials about TensorFlow and Keras. Those are your main tools and eventually, in many cases we were only required to complete the gaps which don't give you a true understanding of how to use those frameworks.
創建者 Jamal H•
The assignments are more like quests - most of the time is spent guessing what is required. The changes made require more programming skills rather than the understanding of ML principles.
The "Attention" topic was not in good detail.
創建者 Heming C•
The programming exercises can be better polished, there was quite a few errors that caused unnecessary confusion to the students. Many times, I felt like I was fighting with the Keras/Tensorflow API rather than solving a ML problem.
創建者 Ben R•
Courses had some issues with the grader, and there were some instances where the expected output in the assignment didn't match the actual output, despite it being correct.
See forums for a range of complaints on the matter.
創建者 Smith R S•
Need more detailed explanation and programming assignments are way too easy.I would suggest to make advanced courses for people to improve their knowledge keeping all this courses also considering not all feel it very easy.
創建者 João H•
Every notebook was super well explained and made except the last one, which was very confusing, unfortunately. I did not enjoy doing that one :( Also, I think the transformers network were not deep explained as hoped.
創建者 Nikhil Y•
Video content is excellent but I am not very much happy with the assignment task. There should must also be some video content based on the assignment because the some codes some libraries are not taught.
創建者 Dominik B•
In comparison with other courses in this specialisation a lot of assignments were poor quality - vague descriptions and code logic (especially week1, asign 2 & 3) or just broken (last week3 assignment)
創建者 Pier L L•
With respect to the others, this one seems to be prepared almost in a hurry and the learning curve is very steep and sometimes the programming assignment don't have a nice progression as the others.
創建者 saipuneet357 .•
Videos were really informative and were equally interesting, but I believe that the programming assignments lacked a bit in clarity. The instructions were really unclear, it could have been better
創建者 Lyn S•
Quite a few bugs or abstractions in this course, in comparison to the others the projects feel a bit rushed and pushed together. Andrews's explanations and video lectures were still great though.
this course is the most difficult in deep learning specification, but i think Andrew NG should design more homework for word embeddings and bidirectional rnn, i do not understand how it works yet
創建者 Egnatious P•
The course was great. However, coming from finance I was also hoping to see some examples which use time series so I can get a picture of how I can extend this knowledge to my specific domain.
創建者 Ioannis B•
The module was really good in explaining the concepts, but there wasn't any deep dive on the equations and mathematics behind with the results of making the code assignment harder to achieve.
創建者 Farzad E•
I gave 5 stars to other courses in this series but this one doesn't deserve 5 stars. There were many typos and bugs in the assignments compared to the other courses of the specialization.
創建者 Rohit B•
Video Lectures were excellent.
Assignments, however, were buggy and spoonfed you too much. I completed them, but on more than one occasion, I had no idea what the code was actually doing.
創建者 Purin W•
The lectures are wonderful as usual but the practical assignments are so extraordinarily perplexing that it does not seem to improve the learner's comprehension by a significant extent.
創建者 Удимов Д А•
Short videos instead of lections.
Copy-paste task instead of exercises.
Loading pretrained models instead of training.
Good full keras tutorial will be ten times more useful.
創建者 Noam S•
The lectures were not as good as the previous andrew ng. courses, and the exercises were quite bad in all honesty.
I do appreciate what I have learned, as the lectures WERE clear enough.