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Kursteilnehmer-Bewertung und -Feedback für Sequence Models von deeplearning.ai

4.8
18,137 Bewertungen
1,964 Bewertungen

Über den Kurs

This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others. You will: - Understand how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs. - Be able to apply sequence models to natural language problems, including text synthesis. - Be able to apply sequence models to audio applications, including speech recognition and music synthesis. This is the fifth and final course of the Deep Learning Specialization. deeplearning.ai is also partnering with the NVIDIA Deep Learning Institute (DLI) in Course 5, Sequence Models, to provide a programming assignment on Machine Translation with deep learning. You will have the opportunity to build a deep learning project with cutting-edge, industry-relevant content....

Top-Bewertungen

AM

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.

JY

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.

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1901 - 1925 von 1,941 Bewertungen für Sequence Models

von 赵凌乔

Sep 20, 2019

The lecture was great but the errors in the programming assignment (especially in formal-typed formulas) really wasted a lot of time and make me confusing at first.

von Bill F

Sep 17, 2019

Toward the end of the specialization, there seemed to be a noticeable drop in both the quality of instruction and the programming assignments. Course 5 on sequence models was much more "hand wavy" than Course 4 on convolution models. At the end of Course 5, I'm still not sure if I learned anything meaningful other than filling in a few blank lines of code to complete the assignment. There was much less intuition provided about the nature of recurrent nets, and then translating that to code was foggy. More attention needs to be paid to how and what the framework is actually doing, not just giving hints at filling the blanks.

Finally, the grader especially in week 3 caused me many, many hours of wasted time and frustration chasing phantom problems in the notebook. Coursera and/or deeplearning.ai does not pay much attention if any to solving the grader or other systemic problems.

von Ragav S

Sep 18, 2019

Would like to learn a bit on how back-prop works when using attention.

von Jorge B S

Sep 23, 2019

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.

von Loic R W

Sep 26, 2019

The course was especially interesting in week 2 and 3, but the assignments for week 1 were confusing and sometimes it was hard to follow where the logic was coming from.

von stdo

Sep 27, 2019

So many errors need to fix.

von Rohit B

Sep 27, 2019

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.

von Natalia O

Oct 04, 2019

in comparison to the previous courses from this sequence, this one is even less structured - ptobably this is because even broader knowledge is tried to be shown in only 3 weeks, but i feel like a lot is skipped between videos (which are ok) and the tasks - in many assignment tasks in this course it is not very well explained what is meant to be done - i mean this especially in case of Keras objects. In many cases it is quite unclear how those classes are supposed to be handled in the context of our task. There are some hints but those are mostly links to documentation (btw, some of the links are no longer up to date), but it is often not too well explained which properties those objects have, what one can do etc. so one ends up with trying using those objects in different configuarations, then googling around, looking on the course forum for the right answer but it is very difficult to derive it. There should be more precise instructions regarding handling Keras objects - the examples in the documentation and in blogs are often much simpler than those from assignments so one ends up not knowing what is going on. In summary - there is a big jump and a big gap between the intuitions in videos (which btw are much more fuzzy than those in first cources in the specialization, the intuitions get more and more superfluous as one doesnt go into detail) and what is being done in the assignments. One thing i really liked about hte previous assignments was that when writing the code one could really know very well what is going on. And this is no longer the case in this course...

von Edoardo B

Nov 15, 2019

Doesn't teach much about keras which is sorely needed

von Mark S

Oct 09, 2019

As we head to the last course in the specialization (and the last two courses are the ones that interested me), we have error after error in the assignments, including problems with the kernel that are not obvious until you've struggled with incoherent stack trace output for a while.

Searching the disorganised discussion centre for the course/week in question you can find that these errors affect everyone and go back for a couple of years, never having been fixed. The mentors there help explain, but mentors cannot edit to fix the code as they do not have permission, and the course supervisors have long since disappeared. So you have to submit incorrect code to pass, then fix the code for your personal private code store - as the fixed code generates the correct numerical answers that unfortunately do not match the numerical answers that the grader requires to pass you!

It feels like, in the hurry to get the full specialization out, the final courses go downhill in terms of care & attention in the rush. Then afterwards, all of the errors and badly designed code in the assignments cause many unexpected headaches, nothing to do with DL, and were never fixed or maintained afterwards by the course supervisors.

In the end, the delays caused to me in the final (two) course(s) added at least one extra monthly payment on to my subscription. Overall I can't complain, the specialization is good. But feels abandoned by the lecturer & assistant lecturers since early 2018

von Jazz

Oct 11, 2019

Should add some instruction videos of Keras

von Adam J

Dec 02, 2019

This course was at a really high-level and barely scratches the surface of Sequence Models. Didn't really go into much detail behind any of the theory, and the programming assignments were mostly done for us, so you don't really end up learning much. You certainly won't be ready to have a job solving NLP problems after taking this course. If you want that, you're better off going through actual college courses online.

von Ar-Em J L

Oct 30, 2019

One of the weaker courses in the specialization. Felt rushed.

von Seng P T P P

Nov 08, 2019

The programming assignments in this course are difficult to implement. The detail descriptions are needed inside the notebooks.

von Marc D

Nov 10, 2019

A good introduction in Sequence models. Unluckily the programming assignments are more of a guess work then real knowledge as there are too few possibilities to check the own code.

von João P B D

Jan 04, 2019

Too difficult.

von zhesihuang

Mar 03, 2019

sucks

von Amir M

Sep 02, 2018

Although the course lectures are great, as are all the lectures in this specialization, some of the assignments have rough edges that need to be smoothed out. It is particularly frustrating for those trying to work on the optional/ungraded programming assignment sections that have some incorrect comparison values, as much time will be wasted trying to figure out the source of the error.

von Ashley H

Sep 14, 2018

Lectures/Videos were excellent, the assignments were very poor (loads of errors in the code not corrected over 7 months since the course went live)

von Mark

Oct 25, 2018

The course videos and the programming assignments were lacking. And there was no support in the forums.

von Mark N

Feb 12, 2018

Poor explanation for alot of things

von SARAVANAN N

Mar 20, 2018

Overall a great course, thanks to Andrew NG for his great explanations. But a very bad support, I faced many issues in submitting the assignment due to technical issues (notebook not saving) but no dedicated resource to help me. I spend lot of time in resolving my self.

von Peter B

Feb 21, 2018

Getting the input parameters correct for the Keras assignments is on par with the satisfaction of dropping a ring, contact lens, or an expensive object into the sink, and spending an hour looking for it inside the disassembled pipes, through built up hair debris and molded dirt.

von Jeffrey S

Jun 02, 2018

Spent more time trying to work around a buggy grader than learning the underlying concepts.

von Alex L

Mar 05, 2018

I feel sad.